---------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/peterdonets/Library/CloudStorage/Dropbox/Replication File for LSSS/replication files PD/log
> /completecodebase.log
  log type:  text
 opened on:  18 May 2023, 10:45:49

. set linesize 120

. 
. 
. cd "/Users/peterdonets/Library/CloudStorage/Dropbox/Replication File for LSSS/replication files PD/dta files PD"
/Users/peterdonets/Library/CloudStorage/Dropbox/Replication File for LSSS/replication files PD/dta files PD

. 
. ***FINCOMPARISON.TXT
. 
. use all_patent_data

. rename patent_id patent

. 
. * Material for Figure 1 and Tables 3, A-5, and A-12
. 
. * Merge in in the academic citations
. 
. merge 1:1 patent using cite

    Result                      Number of obs
    -----------------------------------------
    Not matched                     2,741,008
        from master                 2,739,339  (_merge==1)
        from using                      1,669  (_merge==2)

    Matched                         1,066,355  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(1,669 observations deleted)

. drop _merge

. replace cite=0 if cite==.
(2,739,339 real changes made)

. merge 1:1 patent using citetopq

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,262,433
        from master                 3,261,450  (_merge==1)
        from using                        983  (_merge==2)

    Matched                           544,244  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(983 observations deleted)

. drop _merge

. replace citetopq=0 if citetopq==.
(3,261,450 real changes made)

. merge 1:1 patent using citeeconbus

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,759,255
        from master                 3,759,206  (_merge==1)
        from using                         49  (_merge==2)

    Matched                            46,488  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(49 observations deleted)

. drop _merge

. replace citeeconbus=0 if citeeconbus==.
(3,759,206 real changes made)

. merge 1:1 patent using citeeconbustopq

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,795,886
        from master                 3,795,870  (_merge==1)
        from using                         16  (_merge==2)

    Matched                             9,824  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(16 observations deleted)

. drop _merge

. replace citeeconbustopq=0 if citeeconbustopq==.
(3,795,870 real changes made)

. merge 1:1 patent using citetop3

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,805,003
        from master                 3,805,003  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               691  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(0 observations deleted)

. drop _merge

. replace citetop3=0 if citetop3==.
(3,805,003 real changes made)

. merge 1:1 patent using citepractop3

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,805,017
        from master                 3,805,017  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               677  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(0 observations deleted)

. drop _merge

. replace citetopprac3=0 if citetopprac3==.
(3,805,017 real changes made)

. merge 1:1 patent using citeage

    Result                      Number of obs
    -----------------------------------------
    Not matched                     2,741,008
        from master                 2,739,339  (_merge==1)
        from using                      1,669  (_merge==2)

    Matched                         1,066,355  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(1,669 observations deleted)

. drop _merge

. 
. * Identifying finance patents and academic-heavy classes
. 
. ren patent patent_id

. merge 1:1 patent_id using financial_patent_data_v3

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,781,439
        from master                 3,781,439  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            24,255  (_merge==3)
    -----------------------------------------

. sum _merge

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      _merge |  3,805,694    1.012747    .1591569          1          3

. gen finpat=(_merge==3)

. drop _merge

. merge 1:1 patent_id using university_patent

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,740,310
        from master                 3,728,591  (_merge==1)
        from using                     11,719  (_merge==2)

    Matched                            77,103  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(11,719 observations deleted)

. gen univpat=(_merge==3)

. drop _merge

. gen primary_cpc_tr=substr(primary_cpc,1,4)
(8,078 missing values generated)

. sort primary_cpc_tr

. by primary_cpc_tr: egen cpcaccount=sum(univpat)

. save temp, replace
file temp.dta saved

. by primary_cpc_tr: drop if _n~=1
(3,805,065 observations deleted)

. sort cpcaccount

. list primary_cpc_tr cpcaccount

     +---------------------+
     | primar~r   cpcacc~t |
     |---------------------|
  1. |     A24F          0 |
  2. |     A42C          0 |
  3. |     B41B          0 |
  4. |     B41L          0 |
  5. |     A47K          0 |
     |---------------------|
  6. |     B21G          0 |
  7. |     G16Z          0 |
  8. |     B27M          0 |
  9. |     D01C          0 |
 10. |     F23Q          0 |
     |---------------------|
 11. |     A01L          0 |
 12. |     B27D          0 |
 13. |     B66F          0 |
 14. |     D05C          0 |
 15. |     B41C          0 |
     |---------------------|
 16. |     A61P          0 |
 17. |     B68C          0 |
 18. |     B68B          0 |
 19. |     B67C          0 |
 20. |     A63D          0 |
     |---------------------|
 21. |     B31C          0 |
 22. |     A41G          0 |
 23. |     B27G          0 |
 24. |     C10C          0 |
 25. |     B21H          0 |
     |---------------------|
 26. |     B61H          0 |
 27. |     A24B          0 |
 28. |     B31B          0 |
 29. |     B61G          0 |
 30. |     B27C          0 |
     |---------------------|
 31. |     A47F          0 |
 32. |     C12J          0 |
 33. |     G10C          0 |
 34. |     D21G          0 |
 35. |     B27F          0 |
     |---------------------|
 36. |     B41N          0 |
 37. |     A21C          0 |
 38. |     F23J          0 |
 39. |     B60F          0 |
 40. |     A01F          0 |
     |---------------------|
 41. |     C12C          0 |
 42. |     B27J          0 |
 43. |     C09H          0 |
 44. |     B41G          0 |
 45. |     C12G          0 |
     |---------------------|
 46. |     B60M          0 |
 47. |     B68G          0 |
 48. |     B62C          0 |
 49. |     H05F          0 |
 50. |     B67D          0 |
     |---------------------|
 51. |     D06J          0 |
 52. |     A63K          0 |
 53. |     B44F          0 |
 54. |     D01H          0 |
 55. |     H02B          0 |
     |---------------------|
 56. |     C12F          0 |
 57. |     B60V          0 |
 58. |     G09D          0 |
 59. |     B61C          0 |
 60. |     G07G          0 |
     |---------------------|
 61. |     D21J          0 |
 62. |     A45F          0 |
 63. |     G03D          0 |
 64. |     E02C          0 |
 65. |     C14B          0 |
     |---------------------|
 66. |     B60P          0 |
 67. |     D06L          0 |
 68. |     E21C          0 |
 69. |     C23D          0 |
 70. |     D06G          0 |
     |---------------------|
 71. |     C23G          0 |
 72. |     B25G          0 |
 73. |     F22G          0 |
 74. |     E05C          0 |
 75. |     A23D          0 |
     |---------------------|
 76. |     B42C          0 |
 77. |     B23F          0 |
 78. |     B27H          0 |
 79. |     C12L          0 |
 80. |     B25H          0 |
     |---------------------|
 81. |     D01G          0 |
 82. |     D06H          0 |
 83. |     D03J          0 |
 84. |     D03C          0 |
 85. |     D07B          0 |
     |---------------------|
 86. |     G06C          0 |
 87. |     B21L          0 |
 88. |     A41H          0 |
 89. |     B25C          0 |
 90. |     C10F          0 |
     |---------------------|
 91. |     C12H          0 |
 92. |     A43C          0 |
 93. |     B42F          0 |
 94. |     B66D          0 |
 95. |     F23H          0 |
     |---------------------|
 96. |     C14C          0 |
 97. |     A22B          0 |
 98. |     A46D          0 |
 99. |     F21H          0 |
100. |     D04D          0 |
     |---------------------|
101. |     B21K          0 |
102. |     F16P          0 |
103. |     G10G          0 |
104. |     B27L          0 |
105. |     B04C          0 |
     |---------------------|
106. |     B60D          0 |
107. |     B23G          0 |
108. |     D21F          0 |
109. |     D01B          0 |
110. |     F17B          0 |
     |---------------------|
111. |     A24C          0 |
112. |     G04D          0 |
113. |     F41F          0 |
114. |     C10H          0 |
115. |     B44D          0 |
     |---------------------|
116. |     G10B          0 |
117. |     D02H          0 |
118. |     B42B          0 |
119. |     B43M          0 |
120. |     F16S          0 |
     |---------------------|
121. |     B43K          1 |
122. |     D06Q          1 |
123. |     B30B          1 |
124. |     A47H          1 |
125. |     A01J          1 |
     |---------------------|
126. |     A63J          1 |
127. |     G21D          1 |
128. |     B24D          1 |
129. |     D05B          1 |
130. |     F24V          1 |
     |---------------------|
131. |     D06C          1 |
132. |     F41J          1 |
133. |     C06C          1 |
134. |     B27N          1 |
135. |     B02B          1 |
     |---------------------|
136. |     B65C          1 |
137. |     C06D          1 |
138. |     F23B          1 |
139. |     F16N          1 |
140. |     F16T          1 |
     |---------------------|
141. |     E01H          1 |
142. |     A41F          1 |
143. |     G03C          1 |
144. |     B62L          1 |
145. |     B61F          1 |
     |---------------------|
146. |     F25C          1 |
147. |     C05C          1 |
148. |     F23K          1 |
149. |     D21D          1 |
150. |     B27B          1 |
     |---------------------|
151. |     D02J          1 |
152. |     E21D          1 |
153. |     E04F          1 |
154. |     B27K          1 |
155. |     C13B          1 |
     |---------------------|
156. |     B60S          1 |
157. |     F22D          1 |
158. |     E05G          1 |
159. |     D06N          1 |
160. |     G04C          1 |
     |---------------------|
161. |     A45C          1 |
162. |     D04G          1 |
163. |     D04C          1 |
164. |     C21C          1 |
165. |     C21B          1 |
     |---------------------|
166. |     F28C          1 |
167. |     B65F          1 |
168. |     F41C          1 |
169. |     G06M          1 |
170. |     B62H          1 |
     |---------------------|
171. |     B41K          1 |
172. |     A41C          1 |
173. |     G12B          1 |
174. |     A23P          1 |
175. |     C09F          1 |
     |---------------------|
176. |     B63J          1 |
177. |     F23G          1 |
178. |     G07D          2 |
179. |     A41B          2 |
180. |     B31D          2 |
     |---------------------|
181. |     G04B          2 |
182. |     D04B          2 |
183. |     A43D          2 |
184. |     B62J          2 |
185. |     A63C          2 |
     |---------------------|
186. |     A23F          2 |
187. |     B41D          2 |
188. |     G06J          2 |
189. |     G04G          2 |
190. |     F25J          2 |
     |---------------------|
191. |     F24B          2 |
192. |     A47G          2 |
193. |     B26F          2 |
194. |     B26B          2 |
195. |     G04R          2 |
     |---------------------|
196. |     B67B          2 |
197. |     B61D          2 |
198. |     F23N          2 |
199. |     A23N          2 |
200. |     E03C          2 |
     |---------------------|
201. |     B25D          2 |
202. |     E05D          2 |
203. |     A62C          2 |
204. |     B23C          2 |
205. |     C10K          2 |
     |---------------------|
206. |     D21B          2 |
207. |     D06P          2 |
208. |     A01B          2 |
209. |     H05C          2 |
210. |     F01P          2 |
     |---------------------|
211. |     E06C          2 |
212. |     F03C          2 |
213. |     F21L          2 |
214. |     E03D          2 |
215. |     B21F          2 |
     |---------------------|
216. |     A47D          2 |
217. |     B43L          2 |
218. |     B61B          2 |
219. |     A24D          2 |
220. |     E03F          2 |
     |---------------------|
221. |     F28B          2 |
222. |     A21B          2 |
223. |     B25F          2 |
224. |     B28C          3 |
225. |     B44B          3 |
     |---------------------|
226. |     B65B          3 |
227. |     F28G          3 |
228. |     F01M          3 |
229. |     B31F          3 |
230. |     F27D          3 |
     |---------------------|
231. |     B64F          3 |
232. |     B63C          3 |
233. |     G09C          3 |
234. |     B61J          3 |
235. |     H01K          3 |
     |---------------------|
236. |     F24D          3 |
237. |     A45B          3 |
238. |     E05F          3 |
239. |     F42C          3 |
240. |     F24T          3 |
     |---------------------|
241. |     A47J          3 |
242. |     A63G          3 |
243. |     A45D          3 |
244. |     B66B          3 |
245. |     A43B          3 |
     |---------------------|
246. |     B60H          3 |
247. |     G07B          3 |
248. |     E03B          3 |
249. |     F24H          3 |
250. |     D06F          3 |
     |---------------------|
251. |     B60J          3 |
252. |     F23M          3 |
253. |     C05B          3 |
254. |     E21F          3 |
255. |     G10F          3 |
     |---------------------|
256. |     F27B          3 |
257. |     A21D          4 |
258. |     B24C          4 |
259. |     B44C          4 |
260. |     F41B          4 |
     |---------------------|
261. |     F41G          4 |
262. |     B42D          4 |
263. |     G21F          4 |
264. |     H02G          4 |
265. |     B21B          4 |
     |---------------------|
266. |     F23R          4 |
267. |     F01L          4 |
268. |     A46B          4 |
269. |     B02C          4 |
270. |     F23L          4 |
     |---------------------|
271. |     F01B          4 |
272. |     C08C          4 |
273. |     E01B          4 |
274. |     F22B          4 |
275. |     H03C          4 |
     |---------------------|
276. |     A22C          4 |
277. |     G05G          4 |
278. |     C05F          4 |
279. |     B61K          5 |
280. |     B60C          5 |
     |---------------------|
281. |     F02F          5 |
282. |     B23D          5 |
283. |     B04B          5 |
284. |     C09G          5 |
285. |     B01B          5 |
     |---------------------|
286. |     B22C          5 |
287. |     A62B          5 |
288. |     B28D          5 |
289. |     B61L          5 |
290. |     B07C          5 |
     |---------------------|
291. |     B26D          5 |
292. |     B62B          5 |
293. |     B41F          5 |
294. |     A01C          5 |
295. |     D02G          5 |
     |---------------------|
296. |     E04G          5 |
297. |     F16J          5 |
298. |     F01C          5 |
299. |     B64B          5 |
300. |     B03D          5 |
     |---------------------|
301. |     A42B          5 |
302. |     G21H          5 |
303. |     B21J          5 |
304. |     C01D          5 |
305. |     F16G          5 |
     |---------------------|
306. |     C10J          6 |
307. |     E01C          6 |
308. |     C08H          6 |
309. |     F02N          6 |
310. |     F24C          6 |
     |---------------------|
311. |     A61D          6 |
312. |     A44B          6 |
313. |     B60T          6 |
314. |     E05B          6 |
315. |     A23K          6 |
     |---------------------|
316. |     B28B          6 |
317. |     C07G          6 |
318. |     E01D          6 |
319. |     G07F          6 |
320. |     B60B          6 |
     |---------------------|
321. |     A44C          6 |
322. |     F42D          7 |
323. |     F02G          7 |
324. |     G06E          7 |
325. |     F17D          7 |
     |---------------------|
326. |     B63H          7 |
327. |     B66C          7 |
328. |     H01T          8 |
329. |     F26B          8 |
330. |     B65H          8 |
     |---------------------|
331. |     B09B          8 |
332. |     E04D          8 |
333. |     D06B          8 |
334. |     E02F          8 |
335. |     A63H          8 |
     |---------------------|
336. |     C05D          8 |
337. |     A23B          8 |
338. |     F01K          8 |
339. |     E02B          9 |
340. |     B63G          9 |
     |---------------------|
341. |     A47B          9 |
342. |     C01C          9 |
343. |     A23J          9 |
344. |     C25F          9 |
345. |     C05G          9 |
     |---------------------|
346. |     H03J          9 |
347. |     B62K          9 |
348. |     G10D          9 |
349. |     A62D          9 |
350. |     E04H          9 |
     |---------------------|
351. |     B62M          9 |
352. |     B03B          9 |
353. |     C10B         10 |
354. |     B25B         10 |
355. |     G03G         10 |
     |---------------------|
356. |     F25D         10 |
357. |     B65G         10 |
358. |     B41M         10 |
359. |     F21S         10 |
360. |     B60G         10 |
     |---------------------|
361. |     D21H         10 |
362. |     A01D         10 |
363. |     F41A         10 |
364. |     F16D         11 |
365. |     A23G         11 |
     |---------------------|
366. |     A41D         11 |
367. |     D03D         11 |
368. |     B64D         11 |
369. |     B33Y         11 |
370. |     E04C         11 |
     |---------------------|
371. |     A47C         12 |
372. |     C22F         12 |
373. |     F16M         12 |
374. |     B60Q         12 |
375. |     F04F         13 |
     |---------------------|
376. |     F23D         13 |
377. |     C13K         13 |
378. |     G09F         13 |
379. |     F16B         13 |
380. |     B21C         14 |
     |---------------------|
381. |     C11C         14 |
382. |     C01F         14 |
383. |     A23C         14 |
384. |     B60N         14 |
385. |     B07B         15 |
     |---------------------|
386. |     C09C         15 |
387. |     A01G         15 |
388. |     A47L         15 |
389. |     D21C         15 |
390. |     B63B         15 |
     |---------------------|
391. |     C25C         15 |
392. |     F15D         15 |
393. |     G21C         16 |
394. |     A61J         16 |
395. |     F17C         16 |
     |---------------------|
396. |     G01W         16 |
397. |     C23F         17 |
398. |     F23C         17 |
399. |     B29B         17 |
400. |     F02K         17 |
     |---------------------|
401. |     F02P         17 |
402. |     F15C         17 |
403. |     B23P         17 |
404. |     B05C         17 |
405. |     D04H         18 |
     |---------------------|
406. |     C11B         18 |
407. |     F03H         18 |
408. |     G01G         18 |
409. |     C03B         18 |
410. |     B23B         18 |
     |---------------------|
411. |     B21D         18 |
412. |     B65D         19 |
413. |     H04K         19 |
414. |     F21K         19 |
415. |     G02C         19 |
     |---------------------|
416. |     C11D         20 |
417. |     C21D         20 |
418. |     G07C         20 |
419. |     E02D         20 |
420. |     F03B         20 |
     |---------------------|
421. |     G21G         20 |
422. |     F16L         20 |
423. |     B64G         21 |
424. |     F24S         21 |
425. |     G16C         21 |
     |---------------------|
426. |     B60K         21 |
427. |     F03D         22 |
428. |     E04B         22 |
429. |     B22D         22 |
430. |     B60R         23 |
     |---------------------|
431. |     F04C         23 |
432. |     H01C         23 |
433. |     B09C         23 |
434. |     F02C         23 |
435. |     B23H         23 |
     |---------------------|
436. |     G08C         24 |
437. |     D06M         24 |
438. |     F24F         25 |
439. |     E06B         25 |
440. |     F42B         26 |
     |---------------------|
441. |     F01D         26 |
442. |     G04F         27 |
443. |     B08B         27 |
444. |     C22B         28 |
445. |     F15B         29 |
     |---------------------|
446. |     H01R         29 |
447. |     G06G         29 |
448. |     H02S         29 |
449. |     B24B         30 |
450. |     E01F         31 |
     |---------------------|
451. |     F16F         31 |
452. |     B23Q         31 |
453. |     F41H         32 |
454. |     C12R         32 |
455. |     C12Y         32 |
     |---------------------|
456. |     A23L         33 |
457. |     G10H         33 |
458. |     A61C         33 |
459. |     C07B         34 |
460. |     F02M         34 |
     |---------------------|
461. |     H03D         34 |
462. |     B06B         34 |
463. |     B60W         35 |
464. |     A61G         35 |
465. |     A61Q         35 |
     |---------------------|
466. |     H02H         36 |
467. |     H04H         37 |
468. |     A63F         37 |
469. |     D01D         38 |
470. |     B60L         38 |
     |---------------------|
471. |     C06B         39 |
472. |     B82B         39 |
473. |     G21B         40 |
474. |     B29D         41 |
475. |     G10K         41 |
     |---------------------|
476. |     F28D         41 |
477. |     H04S         42 |
478. |     H03G         43 |
479. |     C09J         43 |
480. |     F16H         43 |
     |---------------------|
481. |     C10L         43 |
482. |     C10M         44 |
483. |     B64C         45 |
484. |     F04D         46 |
485. |     A01M         49 |
     |---------------------|
486. |     F28F         50 |
487. |     C08B         52 |
488. |     G01H         53 |
489. |     H05G         54 |
490. |     C09B         55 |
     |---------------------|
491. |     A63B         55 |
492. |     F02B         55 |
493. |     F16C         55 |
494. |     G21K         56 |
495. |     G16H         56 |
     |---------------------|
496. |     A01H         58 |
497. |     F01N         58 |
498. |     G03B         59 |
499. |     H01H         59 |
500. |     F21V         60 |
     |---------------------|
501. |     C07J         60 |
502. |     G05F         61 |
503. |     F25B         61 |
504. |     F03G         61 |
505. |     B62D         64 |
     |---------------------|
506. |     D01F         65 |
507. |     G01F         66 |
508. |     B05B         67 |
509. |     C03C         68 |
510. |     H04M         68 |
     |---------------------|
511. |     H02P         72 |
512. |     B03C         73 |
513. |     F16K         73 |
514. |     C40B         75 |
515. |     G03H         75 |
     |---------------------|
516. |     G01D         81 |
517. |     A61H         82 |
518. |     G08B         83 |
519. |     G01P         84 |
520. |     F04B         86 |
     |---------------------|
521. |     C10G         87 |
522. |     G01M         87 |
523. |     B01F         88 |
524. |                  90 |
525. |     F02D         91 |
     |---------------------|
526. |     H05H         93 |
527. |     C01G         94 |
528. |     G01K         97 |
529. |     B41J         99 |
530. |     C25D         99 |
     |---------------------|
531. |     B81B         99 |
532. |     C25B        100 |
533. |     E21B        100 |
534. |     C08K        105 |
535. |     H02N        106 |
     |---------------------|
536. |     B22F        109 |
537. |     H03B        109 |
538. |     B05D        113 |
539. |     H04Q        114 |
540. |     H02K        114 |
     |---------------------|
541. |     G08G        121 |
542. |     C22C        122 |
543. |     B23K        123 |
544. |     G05D        124 |
545. |     H03L        131 |
     |---------------------|
546. |     G16B        140 |
547. |     H01F        142 |
548. |     C08L        142 |
549. |     C12M        145 |
550. |     G09B        146 |
     |---------------------|
551. |     G05B        160 |
552. |     C09D        164 |
553. |     H05B        165 |
554. |     G09G        171 |
555. |     C08J        172 |
     |---------------------|
556. |     G01V        174 |
557. |     B25J        177 |
558. |     G01L        182 |
559. |     H01B        182 |
560. |     G01Q        184 |
     |---------------------|
561. |     A01K        187 |
562. |     B32B        192 |
563. |     G01T        199 |
564. |     G06N        208 |
565. |     H03H        211 |
     |---------------------|
566. |     H01P        211 |
567. |     B81C        213 |
568. |     C04B        216 |
569. |     C02F        232 |
570. |     G06Q        234 |
     |---------------------|
571. |     C30B        235 |
572. |     G11B        249 |
573. |     G01C        251 |
574. |     H01G        257 |
575. |     H02J        260 |
     |---------------------|
576. |     A01N        262 |
577. |     H04R        263 |
578. |     H02M        265 |
579. |     H04J        275 |
580. |     B29C        288 |
     |---------------------|
581. |     H05K        296 |
582. |     G01B        303 |
583. |     C07H        304 |
584. |     G10L        309 |
585. |     H03F        340 |
     |---------------------|
586. |     H03K        351 |
587. |     G01J        367 |
588. |     C08F        374 |
589. |     B01L        380 |
590. |     C23C        383 |
     |---------------------|
591. |     G03F        386 |
592. |     G01S        388 |
593. |     C09K        407 |
594. |     C01B        449 |
595. |     A61M        457 |
     |---------------------|
596. |     C08G        479 |
597. |     H01Q        490 |
598. |     C07F        500 |
599. |     C12P        503 |
600. |     A61L        506 |
     |---------------------|
601. |     G11C        508 |
602. |     H03M        524 |
603. |     B01D        561 |
604. |     A61F        578 |
605. |     G02F        640 |
     |---------------------|
606. |     H01S        643 |
607. |     A61N        736 |
608. |     B01J        778 |
609. |     B82Y        856 |
610. |     C07C        883 |
     |---------------------|
611. |     H01J        926 |
612. |     G06K        955 |
613. |     G01R       1069 |
614. |     H01M       1150 |
615. |     G06T       1179 |
     |---------------------|
616. |     H04N       1251 |
617. |     H04B       1338 |
618. |     G02B       1638 |
619. |     H04W       1737 |
620. |     C12Q       1806 |
     |---------------------|
621. |     C07D       2103 |
622. |     A61B       2547 |
623. |     G06F       2745 |
624. |     H04L       2884 |
625. |     C07K       3460 |
     |---------------------|
626. |     C12N       3528 |
627. |     G01N       4911 |
628. |     H01L       4966 |
629. |     A61K       6327 |
     +---------------------+

. use temp, clear

. gen academicclass=(cpcaccount>=500)

. drop cpcaccount

. 
. * Cross-tabs--For Figure 1
. 
. replace app_year=year(app_date)
(3,782,489 real changes made)

. gen aw_year=year(grant_date)

. by app_year, sort: sum finpat

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    197,509    .0053972    .0732675          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2001

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    210,886    .0053821     .073165          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2002

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    210,206    .0050141    .0706329          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2003

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    200,429    .0052887    .0725308          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2004

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    200,036     .005694    .0752435          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    203,575     .006042    .0774953          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2006

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    209,348    .0072654    .0849274          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2007

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    216,704    .0081078    .0896779          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2008

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    218,213    .0073552    .0854467          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2009

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    210,203    .0068791    .0826546          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    221,971    .0077578    .0877361          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2011

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    239,574    .0073672    .0855161          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2012

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    259,948    .0080978    .0896227          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2013

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    267,812    .0062432    .0787669          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2014

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    257,970    .0060356    .0774544          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    226,414    .0051454    .0715471          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2016

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    164,291    .0046381    .0679458          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2017

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     79,995    .0053253    .0727808          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2018

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     10,610     .006409    .0798033          0          1


. by aw_year, sort: sum finpat

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |      1,015           0           0          0          0

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2001

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     36,632    .0010646    .0326119          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2002

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    109,984    .0008456    .0290667          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2003

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    142,614     .001199    .0346065          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2004

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    153,079    .0019206    .0437824          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    137,967    .0028847    .0536325          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2006

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    169,740    .0045069    .0669821          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2007

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    155,735    .0050406    .0708183          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2008

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    156,977    .0068354    .0823937          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2009

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    166,952    .0078286    .0881326          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    219,428    .0103633    .1012717          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2011

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    224,598    .0097864    .0984411          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2012

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    253,494    .0096452    .0977354          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2013

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    278,425    .0105199    .1020258          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2014

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    301,594    .0083324     .090901          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    299,356    .0046366    .0679348          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2016

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    304,113    .0043832    .0660609          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2017

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    319,990    .0057314    .0754891          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2018

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    308,849    .0067768    .0820419          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2019

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     65,152    .0049576    .0702363          0          1


. drop app_date aw_year

. 
. * Academic
. 
. merge 1:1 patent_id using university_patent

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,740,310
        from master                 3,728,591  (_merge==1)
        from using                     11,719  (_merge==2)

    Matched                            77,103  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(11,719 observations deleted)

. gen academic=(_merge==3)

. drop _merge

. 
. * Time period
. 
. gen appyrearly=(app_year<2005)

. gen appyrmid=(app_year>=2005 & app_year<2010)

. gen appyrlate=(app_year>=2010)

. 
. * VC
. 
. ren patent_id patent

. merge 1:m patent using patentvc, keepusing(vc_active2)

    Result                      Number of obs
    -----------------------------------------
    Not matched                     2,740,616
        from master                   626,094  (_merge==1)
        from using                  2,114,522  (_merge==2)

    Matched                         3,302,959  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(2,114,522 observations deleted)

. drop _merge

. sort patent

. by patent: drop if _n~=1
(123,359 observations deleted)

. 
. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      patent |  3,805,694     8310526     1114713    6062457   1.02e+07
  grant_date |  3,805,694     19014.8     1767.49      14746      21620
 primary_cpc |          0
cpc_subclass |          0
  cite_count |  3,805,694    7.217388    26.21994          0       3303
-------------+---------------------------------------------------------
  mean_cites |  3,805,694    7.217388    9.769698          0        424
weighted_c~e |  3,792,460           1    3.093975          0   471.5185
assignee_t~e |  3,530,965    2.543116    .5866309          2         15
kogan_etal~l |  1,325,669    12.11012    32.43701   .0002206   5199.875
kelly_eta~10 |  2,691,606    1.235833    .8096011          0   57.63056
-------------+---------------------------------------------------------
kelly_etal~5 |  2,691,606    .8061168    .3806262          0   40.62791
    csa_code |  1,439,802    364.3801    129.9968        104        566
   csa_title |          0
inventor_1~y |          0
vc_num_deals |  1,435,383    424.2538    570.6337          0       2306
-------------+---------------------------------------------------------
vc_sum_equ~d |  1,435,383    4537.596    7485.268          0   55689.49
us_ai_rank~g |    669,338     2.48615    1.725093          1          6
        cite |  3,805,694    3.676993    20.47579          0       1618
    citetopq |  3,805,694    1.526919    11.92619          0       1020
 citeeconbus |  3,805,694    .0214305    .3715056          0         85
-------------+---------------------------------------------------------
citeeconbu~q |  3,805,694    .0033408     .084257          0         17
    citetop3 |  3,805,694    .0003474     .038276          0         20
citetopprac3 |  3,805,694    .0002651     .027911          0         17
     citeage |  1,066,355    9.608693    7.479083        -18        180
    app_year |  3,805,694    2008.436    4.955624       2000       2018
-------------+---------------------------------------------------------
       state |          0
  state_fips |     19,153    24.71232    16.22884          1         78
assignee_1~y |          0
  accounting |     24,255    .0420914    .1596893          0          1
investment~g |     24,255    .0785083    .2274502          0          1
-------------+---------------------------------------------------------
commercial~g |     24,255    .0504765    .1684729          0          1
communicat~s |     24,255    .1389632    .2737019          0          1
    payments |     24,255    .3731844    .3771753          0          1
cryptocurr~y |     24,255    .0115153    .0670557          0          1
    currency |     24,255    .0057265    .0593467          0          1
-------------+---------------------------------------------------------
   insurance |     24,255    .0132671    .0992131          0          1
 real_estate |     24,255    .0133779     .090717          0          1
retail_ban~g |     24,255    .0606465    .1807701          0          1
    security |     24,255    .1979814    .3110459          0          1
wealth_man~t |     24,255    .0142615    .1015904          0          1
-------------+---------------------------------------------------------
pae_initia~t |     24,255    .0176458    .1316631          0          1
assignee_1~e |          0
pae_reassi~t |     24,255    .0109256    .1039551          0          1
reassignme~e |          0
pae_reassi~e |        265    18763.75    1303.724      14650      21137
-------------+---------------------------------------------------------
    capiq_id |          0
company_name |          0
     revenue |     13,346    29808.75    42680.09          0     485651
      ebitda |     10,353    5460.739    8671.517     -13595      82487
  rd_expense |      5,629    2099.578    2818.713     .05687      28837
-------------+---------------------------------------------------------
advertisin~e |      6,281    765.7837    1072.822       .001   11541.87
  net_income |     13,438    3141.358    6247.718     -99289      53394
        cash |     13,192     16046.1    48444.66    -.04757     331285
long_term_~t |     10,625    49249.73    144512.4    -5.9612    2944357
short_term~t |      8,184    57247.24    118859.5          0    1099811
-------------+---------------------------------------------------------
short_term~s |      9,401    34604.06    105264.5          0     824318
shareholde~y |     13,234    30338.87    53621.34     -50391     267146
  market_cap |     11,411    69433.16    86006.04     .00821   860882.5
  employment |     12,173    93562.38    174450.2          7    2300000
year_founded |     17,659    1945.101    59.14909       1727       2018
-------------+---------------------------------------------------------
 age_of_firm |     17,659    73.89943    59.14909          1        292
 global_sifi |     24,255    .0627912     .242592          0          1
primary_in~y |          0
primary_in~e |          0
gics_secto~e |          0
-------------+---------------------------------------------------------
gics_group~e |          0
gics_indus~e |          0
 gics_sector |          0
gics_indus~s |          0
revenue_gr~p |          0
-------------+---------------------------------------------------------
      public |     24,255    .4704597    .4991369          0          1
   vc_backed |     24,255    .0496392     .217203          0          1
          bs |     23,197    813884.3    450114.8        580    2377940
          fs |     23,197    782923.3    436854.3          0    2374299
    division |          0
-------------+---------------------------------------------------------
      finpat |  3,805,694    .0063733    .0795784          0          1
     univpat |  3,805,694    .0202599    .1408881          0          1
primary_cp~r |          0
academiccl~s |  3,805,694    .4801542    .4996061          0          1
    academic |  3,805,694    .0202599    .1408881          0          1
-------------+---------------------------------------------------------
  appyrearly |  3,805,694     .267774    .4427992          0          1
    appyrmid |  3,805,694    .2780158    .4480213          0          1
   appyrlate |  3,805,694    .4542102    .4978989          0          1
  vc_active2 |  3,179,600     .022266    .1475474          0          1

. 
. * Assigneee type
. 
. gen assignee=2 if (assignee_type==2 | assignee_type==12)
(2,104,656 missing values generated)

. replace assignee=3 if (assignee_type==3 | assignee_type==13)
(1,790,964 real changes made)

. replace assignee=4 if (assignee_type==4 | assignee_type==14 | assignee_type==5 | assignee_type==15 | assignee_type==.)
(296,597 real changes made)

. replace assignee=6 if (assignee_type==6 | assignee_type==8 | assignee_type==9)
(13,749 real changes made)

. replace assignee=7 if (assignee_type==7)
(3,346 real changes made)

. replace assignee=8 if (academic==1 & inventor=="US")
(50,932 real changes made)

. replace assignee=9 if (academic==1 & inventor~="US")
(26,171 real changes made)

. label define asstype1 2 "US Corp" 3 "Foreign Corp" 4 "Individual" 6 "US Govt" 7 "Foreign Govt" 8 "US Univ" 9 "Foreign 
> Univ" 10 "Other"

. label values assignee asstype1

. gen assigneesimple=assignee

. replace assigneesimple=10 if (assignee>=4 & assignee~=8)
(339,613 real changes made)

. label values assigneesimple asstype1

. 
. * Table 3
. 
. tab vc_active2 finpat if vc_active2~=., chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
vc_active2 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,089,558     19,245 | 3,108,803 
           |     97.78      95.98 |     97.77 
-----------+----------------------+----------
         1 |    69,990        807 |    70,797 
           |      2.22       4.02 |      2.23 
-----------+----------------------+----------
     Total | 3,159,548     20,052 | 3,179,600 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) = 299.6335   Pr = 0.000

. tab vc_active2 finpat if vc_active2~=. & inventor=="US", chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
vc_active2 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,413,360     14,978 | 1,428,338 
           |     95.57      95.01 |     95.57 
-----------+----------------------+----------
         1 |    65,493        786 |    66,279 
           |      4.43       4.99 |      4.43 
-----------+----------------------+----------
     Total | 1,478,853     15,764 | 1,494,617 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  11.4357   Pr = 0.001

. tab assignee finpat, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

             |        finpat
    assignee |         0          1 |     Total
-------------+----------------------+----------
     US Corp | 1,631,428     18,181 | 1,649,609 
             |     43.14      74.96 |     43.35 
-------------+----------------------+----------
Foreign Corp | 1,761,648      3,892 | 1,765,540 
             |     46.59      16.05 |     46.39 
-------------+----------------------+----------
  Individual |   294,484      2,099 |   296,583 
             |      7.79       8.65 |      7.79 
-------------+----------------------+----------
     US Govt |    13,530         19 |    13,549 
             |      0.36       0.08 |      0.36 
-------------+----------------------+----------
Foreign Govt |     3,308          2 |     3,310 
             |      0.09       0.01 |      0.09 
-------------+----------------------+----------
     US Univ |    50,885         47 |    50,932 
             |      1.35       0.19 |      1.34 
-------------+----------------------+----------
Foreign Univ |    26,156         15 |    26,171 
             |      0.69       0.06 |      0.69 
-------------+----------------------+----------
       Total | 3,781,439     24,255 | 3,805,694 
             |    100.00     100.00 |    100.00 

. gen assignee2=(assignee==2)

. tab assignee2 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee2 |         0          1 |     Total
-----------+----------------------+----------
         0 | 2,150,011      6,074 | 2,156,085 
           |     56.86      25.04 |     56.65 
-----------+----------------------+----------
         1 | 1,631,428     18,181 | 1,649,609 
           |     43.14      74.96 |     43.35 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  9.9e+03   Pr = 0.000

. gen assignee3=(assignee==3)

. tab assignee3 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee3 |         0          1 |     Total
-----------+----------------------+----------
         0 | 2,019,791     20,363 | 2,040,154 
           |     53.41      83.95 |     53.61 
-----------+----------------------+----------
         1 | 1,761,648      3,892 | 1,765,540 
           |     46.59      16.05 |     46.39 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  9.0e+03   Pr = 0.000

. gen assignee4=(assignee==4)

. tab assignee4 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee4 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,486,955     22,156 | 3,509,111 
           |     92.21      91.35 |     92.21 
-----------+----------------------+----------
         1 |   294,484      2,099 |   296,583 
           |      7.79       8.65 |      7.79 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  25.1683   Pr = 0.000

. gen assignee5=(assignee==5)

. tab assignee5 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee5 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

. gen assignee6=(assignee==6)

. tab assignee6 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee6 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,767,909     24,236 | 3,792,145 
           |     99.64      99.92 |     99.64 
-----------+----------------------+----------
         1 |    13,530         19 |    13,549 
           |      0.36       0.08 |      0.36 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  53.0588   Pr = 0.000

. gen assignee7=(assignee==7)

. tab assignee7 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee7 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,778,131     24,253 | 3,802,384 
           |     99.91      99.99 |     99.91 
-----------+----------------------+----------
         1 |     3,308          2 |     3,310 
           |      0.09       0.01 |      0.09 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  17.4114   Pr = 0.000

. gen assignee8=(assignee==8)

. tab assignee8 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee8 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,730,554     24,208 | 3,754,762 
           |     98.65      99.81 |     98.66 
-----------+----------------------+----------
         1 |    50,885         47 |    50,932 
           |      1.35       0.19 |      1.34 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) = 242.1762   Pr = 0.000

. gen assignee9=(assignee==9)

. tab assignee9 finpat, chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee9 |         0          1 |     Total
-----------+----------------------+----------
         0 | 3,755,283     24,240 | 3,779,523 
           |     99.31      99.94 |     99.31 
-----------+----------------------+----------
         1 |    26,156         15 |    26,171 
           |      0.69       0.06 |      0.69 
-----------+----------------------+----------
     Total | 3,781,439     24,255 | 3,805,694 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) = 139.9946   Pr = 0.000

. 
. * Table A-5
. 
. tab vc_active2 finpat if (vc_active2~=. & (finpat==1 | academicclass==1)), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
vc_active2 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,533,017     19,245 | 1,552,262 
           |     96.75      95.98 |     96.74 
-----------+----------------------+----------
         1 |    51,565        807 |    52,372 
           |      3.25       4.02 |      3.26 
-----------+----------------------+----------
     Total | 1,584,582     20,052 | 1,604,634 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  37.2201   Pr = 0.000

. tab vc_active2 finpat if (vc_active2~=. & inventor=="US" & (finpat==1 | academicclass==1)), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
vc_active2 |         0          1 |     Total
-----------+----------------------+----------
         0 |   728,879     14,978 |   743,857 
           |     93.81      95.01 |     93.83 
-----------+----------------------+----------
         1 |    48,129        786 |    48,915 
           |      6.19       4.99 |      6.17 
-----------+----------------------+----------
     Total |   777,008     15,764 |   792,772 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  38.9507   Pr = 0.000

. tab assignee finpat if (finpat==1 | academicclass==1), col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

             |        finpat
    assignee |         0          1 |     Total
-------------+----------------------+----------
     US Corp |   858,352     18,181 |   876,533 
             |     47.07      74.96 |     47.44 
-------------+----------------------+----------
Foreign Corp |   840,413      3,892 |   844,305 
             |     46.09      16.05 |     45.70 
-------------+----------------------+----------
  Individual |    61,692      2,099 |    63,791 
             |      3.38       8.65 |      3.45 
-------------+----------------------+----------
     US Govt |     6,236         19 |     6,255 
             |      0.34       0.08 |      0.34 
-------------+----------------------+----------
Foreign Govt |     2,016          2 |     2,018 
             |      0.11       0.01 |      0.11 
-------------+----------------------+----------
     US Univ |    37,208         47 |    37,255 
             |      2.04       0.19 |      2.02 
-------------+----------------------+----------
Foreign Univ |    17,503         15 |    17,518 
             |      0.96       0.06 |      0.95 
-------------+----------------------+----------
       Total | 1,823,420     24,255 | 1,847,675 
             |    100.00     100.00 |    100.00 

. tab assignee2 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee2 |         0          1 |     Total
-----------+----------------------+----------
         0 |   965,068      6,074 |   971,142 
           |     52.93      25.04 |     52.56 
-----------+----------------------+----------
         1 |   858,352     18,181 |   876,533 
           |     47.07      74.96 |     47.44 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  7.5e+03   Pr = 0.000

. tab assignee3 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee3 |         0          1 |     Total
-----------+----------------------+----------
         0 |   983,007     20,363 | 1,003,370 
           |     53.91      83.95 |     54.30 
-----------+----------------------+----------
         1 |   840,413      3,892 |   844,305 
           |     46.09      16.05 |     45.70 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  8.7e+03   Pr = 0.000

. tab assignee4 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee4 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,761,728     22,156 | 1,783,884 
           |     96.62      91.35 |     96.55 
-----------+----------------------+----------
         1 |    61,692      2,099 |    63,791 
           |      3.38       8.65 |      3.45 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  2.0e+03   Pr = 0.000

. tab assignee5 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee5 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

. tab assignee6 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee6 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,817,184     24,236 | 1,841,420 
           |     99.66      99.92 |     99.66 
-----------+----------------------+----------
         1 |     6,236         19 |     6,255 
           |      0.34       0.08 |      0.34 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  49.3200   Pr = 0.000

. tab assignee7 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee7 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,821,404     24,253 | 1,845,657 
           |     99.89      99.99 |     99.89 
-----------+----------------------+----------
         1 |     2,016          2 |     2,018 
           |      0.11       0.01 |      0.11 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  22.9682   Pr = 0.000

. tab assignee8 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee8 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,786,212     24,208 | 1,810,420 
           |     97.96      99.81 |     97.98 
-----------+----------------------+----------
         1 |    37,208         47 |    37,255 
           |      2.04       0.19 |      2.02 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) = 413.2217   Pr = 0.000

. tab assignee9 finpat if (finpat==1 | academicclass==1), chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |        finpat
 assignee9 |         0          1 |     Total
-----------+----------------------+----------
         0 | 1,805,917     24,240 | 1,830,157 
           |     99.04      99.94 |     99.05 
-----------+----------------------+----------
         1 |    17,503         15 |    17,518 
           |      0.96       0.06 |      0.95 
-----------+----------------------+----------
     Total | 1,823,420     24,255 | 1,847,675 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) = 205.5645   Pr = 0.000

. 
. drop assignee2-assignee9

. 
. * Table A-12
. 
. reg cite finpat appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   669,338
-------------+----------------------------------   F(4, 669333)    =    193.95
       Model |  701141.534         4  175285.384   Prob > F        =    0.0000
    Residual |   604930929   669,333  903.781719   R-squared       =    0.0012
-------------+----------------------------------   Adj R-squared   =    0.0012
       Total |   605632071   669,337  904.823835   Root MSE        =    30.063

-------------------------------------------------------------------------------
         cite | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
       finpat |   -4.45809   .3364104   -13.25   0.000    -5.117443   -3.798736
   appyrearly |  -2.165423   .0897803   -24.12   0.000    -2.341389   -1.989456
     appyrmid |   -.508875   .0887899    -5.73   0.000    -.6829003   -.3348496
us_ai_ranking |   .0841925   .0213047     3.95   0.000     .0424359    .1259491
        _cons |   7.773756   .0750653   103.56   0.000     7.626631    7.920882
-------------------------------------------------------------------------------

. reg citeeconbus finpat appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   669,338
-------------+----------------------------------   F(4, 669333)    =   2204.90
       Model |  4069.69777         4  1017.42444   Prob > F        =    0.0000
    Residual |  308855.002   669,333  .461436986   R-squared       =    0.0130
-------------+----------------------------------   Adj R-squared   =    0.0130
       Total |    312924.7   669,337  .467514421   Root MSE        =    .67929

-------------------------------------------------------------------------------
  citeeconbus | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
       finpat |   .7107173   .0076014    93.50   0.000     .6958188    .7256158
   appyrearly |   .0022971   .0020286     1.13   0.257    -.0016789    .0062732
     appyrmid |   .0078512   .0020063     3.91   0.000      .003919    .0117834
us_ai_ranking |   .0039061   .0004814     8.11   0.000     .0029626    .0048496
        _cons |   .0351794   .0016961    20.74   0.000      .031855    .0385038
-------------------------------------------------------------------------------

. reg citetop3 finpat appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   669,338
-------------+----------------------------------   F(4, 669333)    =   1778.52
       Model |  41.1337785         4  10.2834446   Prob > F        =    0.0000
    Residual |  3870.09172   669,333  .005782012   R-squared       =    0.0105
-------------+----------------------------------   Adj R-squared   =    0.0105
       Total |   3911.2255   669,337  .005843432   Root MSE        =    .07604

-------------------------------------------------------------------------------
     citetop3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
       finpat |   .0716764   .0008509    84.24   0.000     .0700087    .0733442
   appyrearly |   .0009812   .0002271     4.32   0.000     .0005361    .0014262
     appyrmid |   .0004835   .0002246     2.15   0.031     .0000433    .0009237
us_ai_ranking |  -.0000953   .0000539    -1.77   0.077    -.0002009    .0000103
        _cons |    .000061   .0001899     0.32   0.748    -.0003111    .0004332
-------------------------------------------------------------------------------

. reg citeage finpat appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   282,620
-------------+----------------------------------   F(4, 282615)    =   2797.30
       Model |  477005.529         4  119251.382   Prob > F        =    0.0000
    Residual |  12048115.6   282,615  42.6308426   R-squared       =    0.0381
-------------+----------------------------------   Adj R-squared   =    0.0381
       Total |  12525121.1   282,619  44.3180435   Root MSE        =    6.5292

-------------------------------------------------------------------------------
      citeage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
       finpat |  -.3460366   .1157288    -2.99   0.003    -.5728618   -.1192114
   appyrearly |  -3.074233   .0304872  -100.84   0.000    -3.133987   -3.014479
     appyrmid |  -1.864873   .0291745   -63.92   0.000    -1.922055   -1.807692
us_ai_ranking |  -.0851366    .006917   -12.31   0.000    -.0986938   -.0715794
        _cons |    10.6101   .0249164   425.83   0.000     10.56126    10.65893
-------------------------------------------------------------------------------

. reg cite finpat##b10.assigneesimple appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   669,338
-------------+----------------------------------   F(10, 669327)   =   1369.72
       Model |  12145186.7        10  1214518.67   Prob > F        =    0.0000
    Residual |   593486884   669,327  886.691982   R-squared       =    0.0201
-------------+----------------------------------   Adj R-squared   =    0.0200
       Total |   605632071   669,337  904.823835   Root MSE        =    29.777

---------------------------------------------------------------------------------------
                 cite | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
             1.finpat |  -1.329708   1.035155    -1.28   0.199    -3.358578    .6991622
                      |
       assigneesimple |
             US Corp  |   4.779337   .1233897    38.73   0.000     4.537497    5.021177
        Foreign Corp  |   2.937113   .1778763    16.51   0.000     2.588482    3.285745
             US Univ  |   26.50398   .2371843   111.74   0.000     26.03911    26.96885
                      |
finpat#assigneesimple |
           1#US Corp  |  -2.884927   1.096091    -2.63   0.008    -5.033229   -.7366245
      1#Foreign Corp  |  -1.094653   2.001566    -0.55   0.584    -5.017658    2.828352
           1#US Univ  |  -20.37496   5.629441    -3.62   0.000    -31.40848   -9.341435
                      |
           appyrearly |  -2.016071    .089074   -22.63   0.000    -2.190653   -1.841489
             appyrmid |  -.4485632   .0879624    -5.10   0.000    -.6209667   -.2761597
        us_ai_ranking |   .0580984   .0213442     2.72   0.006     .0162645    .0999322
                _cons |   2.946914   .1395404    21.12   0.000     2.673419    3.220409
---------------------------------------------------------------------------------------

. reg citeeconbus finpat##b10.assigneesimple appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   669,338
-------------+----------------------------------   F(10, 669327)   =    924.87
       Model |  4265.02447        10  426.502447   Prob > F        =    0.0000
    Residual |  308659.675   669,327  .461149297   R-squared       =    0.0136
-------------+----------------------------------   Adj R-squared   =    0.0136
       Total |    312924.7   669,337  .467514421   Root MSE        =    .67908

---------------------------------------------------------------------------------------
          citeeconbus | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
             1.finpat |    .468382   .0236069    19.84   0.000     .4221132    .5146509
                      |
       assigneesimple |
             US Corp  |   .0391576   .0028139    13.92   0.000     .0336423    .0446728
        Foreign Corp  |   .0171183   .0040565     4.22   0.000     .0091677    .0250689
             US Univ  |   .0423151    .005409     7.82   0.000     .0317136    .0529167
                      |
finpat#assigneesimple |
           1#US Corp  |    .278846   .0249966    11.16   0.000     .2298535    .3278385
      1#Foreign Corp  |   .0534879   .0456462     1.17   0.241    -.0359771    .1429529
           1#US Univ  |   .3661029   .1283807     2.85   0.004      .114481    .6177249
                      |
           appyrearly |   .0037874   .0020314     1.86   0.062     -.000194    .0077688
             appyrmid |   .0084559    .002006     4.22   0.000     .0045242    .0123876
        us_ai_ranking |   .0043662   .0004868     8.97   0.000     .0034122    .0053203
                _cons |  -.0001501   .0031823    -0.05   0.962    -.0063872     .006087
---------------------------------------------------------------------------------------

. reg citetop3 finpat##b10.assigneesimple appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   669,338
-------------+----------------------------------   F(10, 669327)   =    740.97
       Model |  42.8246958        10  4.28246958   Prob > F        =    0.0000
    Residual |  3868.40081   669,327  .005779538   R-squared       =    0.0109
-------------+----------------------------------   Adj R-squared   =    0.0109
       Total |   3911.2255   669,337  .005843432   Root MSE        =    .07602

---------------------------------------------------------------------------------------
             citetop3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
             1.finpat |   .0404407   .0026428    15.30   0.000     .0352609    .0456205
                      |
       assigneesimple |
             US Corp  |   .0000997    .000315     0.32   0.752    -.0005178    .0007171
        Foreign Corp  |  -.0001107   .0004541    -0.24   0.807    -.0010007    .0007794
             US Univ  |   .0000885   .0006055     0.15   0.884    -.0010983    .0012754
                      |
finpat#assigneesimple |
           1#US Corp  |   .0370241   .0027984    13.23   0.000     .0315394    .0425088
      1#Foreign Corp  |  -.0142155   .0051101    -2.78   0.005    -.0242311   -.0041999
           1#US Univ  |   .0282991   .0143723     1.97   0.049     .0001299    .0564682
                      |
           appyrearly |   .0010063   .0002274     4.42   0.000     .0005606     .001452
             appyrmid |   .0004974   .0002246     2.21   0.027     .0000572    .0009375
        us_ai_ranking |  -.0000931   .0000545    -1.71   0.088    -.0001999    .0000137
                _cons |  -.0000279   .0003563    -0.08   0.938    -.0007262    .0006703
---------------------------------------------------------------------------------------

. reg citeage finpat##b10.assigneesimple appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   282,620
-------------+----------------------------------   F(10, 282609)   =   1170.46
       Model |  498113.671        10  49811.3671   Prob > F        =    0.0000
    Residual |  12027007.5   282,609  42.5570575   R-squared       =    0.0398
-------------+----------------------------------   Adj R-squared   =    0.0397
       Total |  12525121.1   282,619  44.3180435   Root MSE        =    6.5236

---------------------------------------------------------------------------------------
              citeage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
             1.finpat |  -.4150944   .4216603    -0.98   0.325    -1.241537     .411348
                      |
       assigneesimple |
             US Corp  |  -.9508158    .059793   -15.90   0.000    -1.068009   -.8336232
        Foreign Corp  |  -1.604491   .0740517   -21.67   0.000     -1.74963   -1.459351
             US Univ  |  -1.151967   .0768367   -14.99   0.000    -1.302565    -1.00137
                      |
finpat#assigneesimple |
           1#US Corp  |   .0274912   .4394541     0.06   0.950    -.8338267     .888809
      1#Foreign Corp  |  -.4907476   .6925068    -0.71   0.479    -1.848042    .8665466
           1#US Univ  |   .9802937   1.425019     0.69   0.492    -1.812703    3.773291
                      |
           appyrearly |  -3.098692   .0304831  -101.65   0.000    -3.158438   -3.038946
             appyrmid |  -1.865661   .0291521   -64.00   0.000    -1.922798   -1.808523
        us_ai_ranking |  -.1040269   .0069856   -14.89   0.000    -.1177184   -.0903354
                _cons |    11.6328   .0638201   182.27   0.000     11.50772    11.75789
---------------------------------------------------------------------------------------

. reg cite finpat##vc_active2 appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   549,827
-------------+----------------------------------   F(6, 549820)    =    461.62
       Model |  2641088.84         6  440181.474   Prob > F        =    0.0000
    Residual |   524283260   549,820  953.554363   R-squared       =    0.0050
-------------+----------------------------------   Adj R-squared   =    0.0050
       Total |   526924349   549,826  958.347457   Root MSE        =     30.88

-----------------------------------------------------------------------------------
             cite | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         1.finpat |  -4.235049   .4002228   -10.58   0.000    -5.019473   -3.450625
     1.vc_active2 |   7.185037   .1629173    44.10   0.000     6.865724    7.504349
                  |
finpat#vc_active2 |
             1 1  |  -6.097791   1.479284    -4.12   0.000    -8.997142   -3.198441
                  |
       appyrearly |  -2.534368   .1014996   -24.97   0.000    -2.733304   -2.335432
         appyrmid |  -.8570558   .0997015    -8.60   0.000    -1.052468   -.6616441
    us_ai_ranking |   .3357135   .0241871    13.88   0.000     .2883076    .3831195
            _cons |   7.499281   .0881853    85.04   0.000      7.32644    7.672121
-----------------------------------------------------------------------------------

. reg citeeconbus finpat##vc_active2 appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   549,827
-------------+----------------------------------   F(6, 549820)    =   1356.58
       Model |  4169.98481         6  694.997468   Prob > F        =    0.0000
    Residual |  281680.725   549,820  .512314439   R-squared       =    0.0146
-------------+----------------------------------   Adj R-squared   =    0.0146
       Total |  285850.709   549,826  .519893038   Root MSE        =    .71576

-----------------------------------------------------------------------------------
      citeeconbus | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         1.finpat |    .801288   .0092768    86.38   0.000     .7831058    .8194702
     1.vc_active2 |   .0212114   .0037763     5.62   0.000       .01381    .0286128
                  |
finpat#vc_active2 |
             1 1  |  -.0230046   .0342884    -0.67   0.502    -.0902087    .0441996
                  |
       appyrearly |   -.000131   .0023527    -0.06   0.956    -.0047421    .0044802
         appyrmid |   .0033083    .002311     1.43   0.152    -.0012212    .0078377
    us_ai_ranking |   .0055684   .0005606     9.93   0.000     .0044696    .0066672
            _cons |   .0354475   .0020441    17.34   0.000     .0314412    .0394538
-----------------------------------------------------------------------------------

. reg citetop3 finpat##vc_active2 appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   549,827
-------------+----------------------------------   F(6, 549820)    =   1100.58
       Model |  44.8266601         6  7.47111002   Prob > F        =    0.0000
    Residual |  3732.37146   549,820  .006788352   R-squared       =    0.0119
-------------+----------------------------------   Adj R-squared   =    0.0119
       Total |  3777.19812   549,826  .006869806   Root MSE        =    .08239

-----------------------------------------------------------------------------------
         citetop3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         1.finpat |   .0791141   .0010679    74.09   0.000     .0770211    .0812071
     1.vc_active2 |  -.0003161   .0004347    -0.73   0.467    -.0011681    .0005358
                  |
finpat#vc_active2 |
             1 1  |   .0470207   .0039469    11.91   0.000     .0392848    .0547566
                  |
       appyrearly |   .0010087   .0002708     3.72   0.000      .000478    .0015395
         appyrmid |   .0003801    .000266     1.43   0.153    -.0001413    .0009015
    us_ai_ranking |  -.0001054   .0000645    -1.63   0.102    -.0002319    .0000211
            _cons |   .0001126   .0002353     0.48   0.632    -.0003485    .0005738
-----------------------------------------------------------------------------------

. reg citeage finpat##vc_active2 appyrearly appyrmid us

      Source |       SS           df       MS      Number of obs   =   252,173
-------------+----------------------------------   F(6, 252166)    =   1706.56
       Model |  417150.643         6  69525.1071   Prob > F        =    0.0000
    Residual |  10273244.5   252,166  40.7400065   R-squared       =    0.0390
-------------+----------------------------------   Adj R-squared   =    0.0390
       Total |  10690395.1   252,172  42.3932678   Root MSE        =    6.3828

-----------------------------------------------------------------------------------
          citeage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         1.finpat |  -.0449539   .1259463    -0.36   0.721    -.2918052    .2018975
     1.vc_active2 |   .5256767   .0454671    11.56   0.000     .4365623    .6147911
                  |
finpat#vc_active2 |
             1 1  |   -4.56995   .4761502    -9.60   0.000    -5.503192   -3.636708
                  |
       appyrearly |  -3.051471   .0314032   -97.17   0.000     -3.11302   -2.989921
         appyrmid |  -1.803905   .0300956   -59.94   0.000    -1.862891   -1.744918
    us_ai_ranking |  -.0837616   .0071647   -11.69   0.000    -.0978042    -.069719
            _cons |   10.46959    .026818   390.39   0.000     10.41703    10.52216
-----------------------------------------------------------------------------------

. 
. 
. ***FINCOMPARISON2.TXT
. 
. * This has materials for Figures 4 (Panel B) and 5, Tables 4, 6, A-6, A-9, A-16 and A-22
. * just looking at finance patents
. 
. clear 

. 
. use financial_patent_data_v3, clear

. ren patent_id patent

. 
. * Consolidating in the categories
. 
. ** 6 industries
. 
. gen bank=(primary_industry=="Diversified Banks" | primary_industry=="Regional Banks" | primary_industry=="Thrifts and 
> Mortgage Finance")

. gen capmkt=(primary_industry=="Asset Management and Custody Banks" | primary_industry=="Diversified Capital Markets" |
>  primary_industry=="Diversified REITs" | primary_industry=="Financial Exchanges and Data" | primary_industry=="Investm
> ent Banking and Brokerage" | primary_industry=="Specialized REITs") 

. gen consfin=(primary_industry=="Consumer Finance" | primary_industry=="Specialized Finance")

. gen insur=(primary_industry=="Life and Health Insurance" | primary_industry=="Multi-line Insurance" | primary_industry
> =="Property and Casualty Insurance" | primary_industry=="Reinsurance")

. gen pay=(primary_industry=="Data Processing and Outsourced Services")

. gen it=(primary_industry=="Application Software" | primary_industry=="Communications Equipment" | primary_industry=="C
> onsumer Electronics" | primary_industry=="Electrical Components and Equipment" | primary_industry=="Electronic Compone
> nts")

. replace it=1 if (primary_industry=="IT Consulting and Other Services" | primary_industry=="Electronic Equipment and In
> struments" | primary_industry=="Electronic Manufacturing Services" | primary_industry=="Integrated Telecommunication S
> ervices" | primary_industry=="Interactive Media and Services")
(1,967 real changes made)

. replace it=1 if (primary_industry=="Internet Services and Infrastructure" | primary_industry=="Internet and Direct Mar
> keting Retail" | primary_industry=="Semiconductor Equipment" | primary_industry=="Semiconductors" | primary_industry==
> "Specialized Consumer Services" | primary_industry=="Systems Software")
(1,862 real changes made)

. replace it=1 if (primary_industry=="Technology Distributors" | primary_industry=="Technology Hardware, Storage and Per
> ipherals" | primary_industry=="Wireless Telecommunication Services")
(1,883 real changes made)

. gen otherind=(bank==0 & capmkt==0 & consfin==0 & insur==0 & pay==0 & it==0)

. 
. ** Figure 4, Panel B
. 
. sum bank capmkt consfin insur pay it otherind

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        bank |     24,255     .066007    .2482995          0          1
      capmkt |     24,255    .0667079    .2495206          0          1
     consfin |     24,255    .0294785    .1691469          0          1
       insur |     24,255     .045269    .2078978          0          1
         pay |     24,255    .0985364    .2980447          0          1
-------------+---------------------------------------------------------
          it |     24,255    .3734075    .4837189          0          1
    otherind |     24,255    .3205937    .4667144          0          1

. 
. **** Simplifying classes
. 
. gen oldcapmkt=capmkt

. gen oldit=it

. replace capmkt=1 if (consfin==1 | insur==1)
(1,813 real changes made)

. replace it=1 if otherind==1
(7,776 real changes made)

. 
. * 3 applications
. 
. gen payapp=(payments>=0.5)

. gen bankapp=(commercial_banking+investment_banking+retail_banking>=0.5)

. gen otherapp=(bankapp~=1 & payapp~=1)

. gen apptype=1 if payapp==1
(13,601 missing values generated)

. replace apptype=2 if bankapp==1
(5,486 real changes made)

. replace apptype=3 if apptype==.
(9,924 real changes made)

. label define apptype1 1 "payments" 2 "banking" 3 "otherapp"

. label values apptype apptype1

. 
. * 2 geographies
. 
. gen us=(inventor_1_country=="US")

. gen othernation=(us==0)

. gen nationtype=1 if us==1
(5,103 missing values generated)

. replace nationtype=2 if nationtype==.
(5,103 real changes made)

. label define nationtype1 1 "us" 2 "not us"

. label values nationtype nationtype1 

. 
. * Academic
. 
. rename patent patent_id

. merge 1:1 patent_id using university_patent

    Result                      Number of obs
    -----------------------------------------
    Not matched                       112,953
        from master                    24,193  (_merge==1)
        from using                     88,760  (_merge==2)

    Matched                                62  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(88,760 observations deleted)

. gen academic=(_merge==3)

. drop _merge

. gen noncorporate=((assignee_type>=4 & assignee_type<=7) | assignee_type==.)

. replace revenue=revenue/1000000
(13,308 real changes made)

. 
. * Time period
. 
. gen app_period=2000 if (app_year<2005)
(18,938 missing values generated)

. replace app_period=2005 if (app_year>=2005 & app_year<2010)
(7,564 real changes made)

. replace app_period=2010 if (app_year>=2010 & app_year<2015)
(8,881 real changes made)

. replace app_period=2015 if (app_year>=2015 & app_year<2019)
(2,493 real changes made)

. gen appyrearly=(app_period==2000)

. gen appyrlate=(app_period==2015)

. 
. * Process--UNsused
. 
. merge m:1 patent_id using process

    Result                      Number of obs
    -----------------------------------------
    Not matched                             3
        from master                         3  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            24,252  (_merge==3)
    -----------------------------------------

. sum process_count_2-abstract_process_use_pred

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
process_co~2 |     19,919    10.32662    11.49302          0        202
proc~t_2_ind |     19,918    1.093182    1.350787          0         29
process_co~5 |     19,919    11.43079    11.55474          0        202
proc~t_5_ind |     19,918    1.420876    1.387128          0         29
proce~t_pred |     19,917    11.63358    11.65075          0        202
-------------+---------------------------------------------------------
p~t_pred_ind |     19,916    2.457973    1.966067          0         40
   use_count |     19,919    .0006526    .0324638          0          2
use_count_~d |     19,918    .0002008    .0141701          0          1
product_~t_2 |     19,919    .0030122    .0755936          0          5
prod~t_2_ind |     19,918    .0010041     .037481          0          3
-------------+---------------------------------------------------------
 total_count |     19,919    22.47683     16.3989          1        437
total_coun~d |     19,918    3.156642    2.108319          1         41
process_ra~2 |     19,919    .4540145    .3435343          0          1
proc~o_2_ind |     19,918    .3545943     .339057          0          1
process_ra~5 |     19,919    .5085597    .3321751          0          1
-------------+---------------------------------------------------------
proc~o_5_ind |     19,918    .4624629    .3156146          0          1
proce~o_pred |     19,917    .5193031    .3349649          0          1
p~o_pred_ind |     19,916    .7777461    .3191249          0          1
   use_ratio |     19,919    .0000287    .0014869          0   .1111111
use_ratio_~d |     19,918    .0000853    .0079848          0          1
-------------+---------------------------------------------------------
product_~o_2 |     19,919    .0001691    .0045998          0   .3333333
prod~o_2_ind |     19,918    .0004142    .0166891          0          1
title_proc~s |          0
   title_use |          0
abstract_p~s |          0
-------------+---------------------------------------------------------
abstract_use |          0
abstract_p~d |          0

. replace process_ratio_2_ind=1 if (communications==1 | security==1)
(3,229 real changes made)

. drop assignee_1-process_ratio_2

. drop process_ratio_5-_merge

. ren process_ratio_2_ind process

. sum process

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     process |     20,603    .4656264    .3949157          0          1

. gen itpay=(it==1 | pay==1)

. 
. * Fintech
. 
. gen fintech=(crypto+payments+security)>0

. sum fintech

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     fintech |     24,255    .7786848    .4151408          0          1

. 
. * Consumer
. 
. merge m:1 patent_id using consumer

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                            24,255  (_merge==3)
    -----------------------------------------

. sum Top100_Keywords

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
Top100_Key~s |     24,255    .2420532    .5569677          0          7

. drop _merge

. 
. * Software
. 
. merge m:m patent_id using software

    Result                      Number of obs
    -----------------------------------------
    Not matched                     7,205,573
        from master                         2  (_merge==1)
        from using                  7,205,571  (_merge==2)

    Matched                            24,253  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(7,205,571 observations deleted)

. drop patent_number _merge

. sum software

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    software |     24,123    .8654811    .3412161          0          1

. 
. * Fintech/Process/software analysis
. 
. ** Table 6, Panels A and B
. 
. reg fintech app_year, r

Linear regression                               Number of obs     =     24,255
                                                F(1, 24253)       =      12.28
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0005
                                                Root MSE          =     .41504

------------------------------------------------------------------------------
             |               Robust
     fintech | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    app_year |   .0020224    .000577     3.50   0.000     .0008914    .0031534
       _cons |   -3.28362   1.159145    -2.83   0.005    -5.555616   -1.011624
------------------------------------------------------------------------------

. reg fintech itpay bank appyrearly appyrlate, r

Linear regression                               Number of obs     =     24,255
                                                F(4, 24250)       =      61.44
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0121
                                                Root MSE          =     .41265

------------------------------------------------------------------------------
             |               Robust
     fintech | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       itpay |   .1262431   .0085611    14.75   0.000     .1094628    .1430234
        bank |   .1424979   .0126345    11.28   0.000     .1177335    .1672623
  appyrearly |  -.0190014   .0066556    -2.85   0.004    -.0320469   -.0059559
   appyrlate |    .017135   .0085004     2.02   0.044     .0004736    .0337964
       _cons |   .6716307   .0081738    82.17   0.000     .6556095    .6876519
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  itpay - bank = 0

       F(  1, 24250) =    2.56
            Prob > F =    0.1099

. reg fintech bank itpay app_year us age noncorporate global_sifi academic public, r

Linear regression                               Number of obs     =     17,659
                                                F(9, 17649)       =      32.19
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0186
                                                Root MSE          =     .40909

------------------------------------------------------------------------------
             |               Robust
     fintech | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |   .1004875   .0186131     5.40   0.000      .064004     .136971
       itpay |   .1407451   .0097506    14.43   0.000     .1216329    .1598572
    app_year |   .0029186   .0006824     4.28   0.000     .0015811    .0042562
          us |    .001354   .0078241     0.17   0.863    -.0139821    .0166901
 age_of_firm |   .0000605   .0000675     0.90   0.370    -.0000719    .0001929
noncorporate |   .0315245   .0543207     0.58   0.562    -.0749493    .1379984
 global_sifi |   .0427508   .0191804     2.23   0.026     .0051553    .0803463
    academic |   .1078397   .0480752     2.24   0.025     .0136075    .2020719
      public |   .0187044   .0071386     2.62   0.009      .004712    .0326968
       _cons |  -5.213386   1.370618    -3.80   0.000    -7.899933   -2.526839
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  - bank + itpay = 0

       F(  1, 17649) =    4.46
            Prob > F =    0.0347

. gen bankyear=bank*app_year

. gen itpayyear=itpay*app_year

. reg fintech bank itpay app_year bankyear itpayyear us age noncorporate global_sifi academic public, r

Linear regression                               Number of obs     =     17,659
                                                F(11, 17647)      =      29.07
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0204
                                                Root MSE          =     .40874

------------------------------------------------------------------------------
             |               Robust
     fintech | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |  -27.71723   6.375696    -4.35   0.000    -40.21423   -15.22024
       itpay |  -20.12065   4.258718    -4.72   0.000    -28.46815   -11.77314
    app_year |  -.0057979   .0019716    -2.94   0.003    -.0096624   -.0019334
    bankyear |   .0138519    .003174     4.36   0.000     .0076306    .0200732
   itpayyear |   .0100875   .0021204     4.76   0.000     .0059314    .0142436
          us |   .0014278   .0078307     0.18   0.855    -.0139212    .0167768
 age_of_firm |   .0001232    .000068     1.81   0.070    -.0000101    .0002564
noncorporate |   .0270944   .0542881     0.50   0.618    -.0793156    .1335044
 global_sifi |   .0219875   .0195466     1.12   0.261    -.0163258    .0603008
    academic |   .1070385   .0480911     2.23   0.026     .0127752    .2013018
      public |    .016646   .0071411     2.33   0.020     .0026486    .0306433
       _cons |   12.29181   3.959577     3.10   0.002     4.530653    20.05297
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  - bank + itpay = 0

       F(  1, 17647) =    2.19
            Prob > F =    0.1389

. test bankyear=itpayyear

 ( 1)  bankyear - itpayyear = 0

       F(  1, 17647) =    2.17
            Prob > F =    0.1406

. reg Top100_Keywords app_year, r

Linear regression                               Number of obs     =     24,255
                                                F(1, 24253)       =      10.72
                                                Prob > F          =     0.0011
                                                R-squared         =     0.0004
                                                Root MSE          =     .55686

------------------------------------------------------------------------------
             |               Robust
Top100_Key~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    app_year |   .0025181   .0007692     3.27   0.001     .0010105    .0040257
       _cons |  -4.815911   1.544686    -3.12   0.002    -7.843591   -1.788231
------------------------------------------------------------------------------

. reg Top100_Keywords itpay bank appyrearly appyrlate, r

Linear regression                               Number of obs     =     24,255
                                                F(4, 24250)       =       5.71
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0009
                                                Root MSE          =     .55677

------------------------------------------------------------------------------
             |               Robust
Top100_Key~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       itpay |   .0358059    .009709     3.69   0.000     .0167756    .0548362
        bank |   .0365695   .0169901     2.15   0.031     .0032678    .0698712
  appyrearly |  -.0268031   .0084391    -3.18   0.001    -.0433442   -.0102619
   appyrlate |  -.0025474   .0126668    -0.20   0.841     -.027375    .0222802
       _cons |   .2173992   .0090679    23.97   0.000     .1996256    .2351727
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  itpay - bank = 0

       F(  1, 24250) =    0.00
            Prob > F =    0.9597

. reg Top100_Keywords bank itpay app_year us age noncorporate global_sifi academic public, r

Linear regression                               Number of obs     =     17,659
                                                F(9, 17649)       =      29.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0089
                                                Root MSE          =     .55507

------------------------------------------------------------------------------
             |               Robust
Top100_Key~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |   .0371777    .017282     2.15   0.031     .0033033    .0710521
       itpay |   .0740374   .0116011     6.38   0.000      .051298    .0967768
    app_year |   .0040643   .0008939     4.55   0.000     .0023122    .0058163
          us |   .1001696    .009832    10.19   0.000     .0808978    .1194413
 age_of_firm |   .0005612   .0000861     6.52   0.000     .0003924    .0007299
noncorporate |  -.2119721   .0324116    -6.54   0.000    -.2755021   -.1484422
 global_sifi |  -.0513788   .0178866    -2.87   0.004    -.0864382   -.0163194
    academic |   -.241357   .0285504    -8.45   0.000    -.2973185   -.1853954
      public |  -.0047374   .0095519    -0.50   0.620    -.0234601    .0139852
       _cons |  -8.093839   1.795131    -4.51   0.000    -11.61247   -4.575206
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  - bank + itpay = 0

       F(  1, 17649) =    4.12
            Prob > F =    0.0425

. reg Top100_Keywords bank itpay app_year bankyear itpayyear us age noncorporate global_sifi academic public, r

Linear regression                               Number of obs     =     17,659
                                                F(11, 17647)      =      24.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0094
                                                Root MSE          =     .55497

------------------------------------------------------------------------------
             |               Robust
Top100_Key~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |  -3.226375   8.405111    -0.38   0.701    -19.70122    13.24847
       itpay |  -13.80454   4.817397    -2.87   0.004    -23.24711   -4.361971
    app_year |  -.0012924   .0021512    -0.60   0.548     -.005509    .0029243
    bankyear |   .0016275    .004184     0.39   0.697    -.0065736    .0098286
   itpayyear |   .0069099   .0023985     2.88   0.004     .0022085    .0116113
          us |   .0993938    .009837    10.10   0.000     .0801124    .1186752
 age_of_firm |   .0005993   .0000871     6.88   0.000     .0004286      .00077
noncorporate |  -.2168031   .0327654    -6.62   0.000    -.2810265   -.1525796
 global_sifi |  -.0569118   .0187371    -3.04   0.002    -.0936384   -.0201851
    academic |  -.2399953   .0289166    -8.30   0.000    -.2966746   -.1833159
      public |  -.0058756   .0095197    -0.62   0.537    -.0245352    .0127839
       _cons |   2.663734   4.319913     0.62   0.537     -5.80372    11.13119
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  - bank + itpay = 0

       F(  1, 17647) =    2.05
            Prob > F =    0.1521

. test bankyear=itpayyear

 ( 1)  bankyear - itpayyear = 0

       F(  1, 17647) =    2.07
            Prob > F =    0.1507

. 
. ** Table A-9
. 
. reg software app_year, r

Linear regression                               Number of obs     =     24,123
                                                F(1, 24121)       =     428.01
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0186
                                                Root MSE          =     .33804

------------------------------------------------------------------------------
             |               Robust
    software | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    app_year |   .0101044   .0004884    20.69   0.000     .0091471    .0110617
       _cons |   -19.4305   .9816462   -19.79   0.000    -21.35459   -17.50641
------------------------------------------------------------------------------

. reg software itpay bank appyrearly appyrlate, r

Linear regression                               Number of obs     =     24,123
                                                F(4, 24118)       =     114.80
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0190
                                                Root MSE          =     .33798

------------------------------------------------------------------------------
             |               Robust
    software | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       itpay |  -.0663192   .0052389   -12.66   0.000    -.0765878   -.0560507
        bank |  -.0373619   .0089848    -4.16   0.000    -.0549727   -.0197512
  appyrearly |  -.0855721   .0061042   -14.02   0.000    -.0975367   -.0736074
   appyrlate |    .043954   .0059882     7.34   0.000     .0322168    .0556913
       _cons |   .9349249   .0047268   197.79   0.000       .92566    .9441897
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  itpay - bank = 0

       F(  1, 24118) =   12.70
            Prob > F =    0.0004

. reg software bank itpay app_year us age noncorporate global_sifi academic public, r

Linear regression                               Number of obs     =     17,552
                                                F(9, 17542)       =      91.69
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0610
                                                Root MSE          =     .32088

------------------------------------------------------------------------------
             |               Robust
    software | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |  -.0607154   .0124396    -4.88   0.000    -.0850983   -.0363326
       itpay |  -.0358227   .0063269    -5.66   0.000    -.0482241   -.0234214
    app_year |    .010126   .0005547    18.26   0.000     .0090389    .0112132
          us |   .1499042   .0078138    19.18   0.000     .1345884      .16522
 age_of_firm |   -.000098   .0000538    -1.82   0.069    -.0002035    7.54e-06
noncorporate |   .0647897   .0393709     1.65   0.100    -.0123812    .1419606
 global_sifi |   .0202945   .0121838     1.67   0.096     -.003587     .044176
    academic |  -.1862114   .0760401    -2.45   0.014    -.3352575   -.0371653
      public |   .0317915   .0058138     5.47   0.000     .0203959    .0431872
       _cons |   -19.5694    1.11464   -17.56   0.000    -21.75421    -17.3846
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  - bank + itpay = 0

       F(  1, 17542) =    3.46
            Prob > F =    0.0629

. reg software bank itpay app_year bankyear itpayyear us age noncorporate global_sifi academic public, r

Linear regression                               Number of obs     =     17,552
                                                F(11, 17540)      =      76.41
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0616
                                                Root MSE          =     .32079

------------------------------------------------------------------------------
             |               Robust
    software | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |  -15.67439   4.677689    -3.35   0.001    -24.84313    -6.50566
       itpay |  -8.887793   2.747595    -3.23   0.001    -14.27335   -3.502234
    app_year |   .0061795   .0011936     5.18   0.000     .0038399    .0085192
    bankyear |   .0077744   .0023274     3.34   0.001     .0032124    .0123364
   itpayyear |   .0044071   .0013671     3.22   0.001     .0017274    .0070868
          us |   .1501233   .0078094    19.22   0.000     .1348161    .1654306
 age_of_firm |  -.0000694   .0000541    -1.28   0.200    -.0001755    .0000367
noncorporate |    .063243   .0392902     1.61   0.107    -.0137697    .1402557
 global_sifi |   .0093397   .0127485     0.73   0.464    -.0156487    .0343281
    academic |  -.1870028    .076004    -2.46   0.014    -.3359782   -.0380274
      public |   .0308521   .0058205     5.30   0.000     .0194433    .0422608
       _cons |  -11.64389   2.398785    -4.85   0.000    -16.34575   -6.942037
------------------------------------------------------------------------------

. test itpay=bank

 ( 1)  - bank + itpay = 0

       F(  1, 17540) =    2.70
            Prob > F =    0.1001

. test bankyear=itpayyear

 ( 1)  bankyear - itpayyear = 0

       F(  1, 17540) =    2.69
            Prob > F =    0.1010

. 
. * Identifying patents for Figure 5
. 
. gsort -cite_count

. list patent_id if _n==1

       +----------+
       | patent~d |
       |----------|
    1. |  6772132 |
       +----------+

. gsort -kogan

. list patent_id if _n==1

       +----------+
       | patent~d |
       |----------|
    1. |  7575157 |
       +----------+

. gsort -kelly_etal_val_5

. list patent_id if _n==1

       +----------+
       | patent~d |
       |----------|
    1. |  7461021 |
       +----------+

. 
. egen weighttile=xtile(weighted),by(app_period) nq(100)
(3 missing values generated)

. egen kogantile=xtile(kogan),by(app_period) nq(100)
(14,756 missing values generated)

. egen kellytile=xtile(kelly_etal_val_5),by(app_period) nq(100)
(6,100 missing values generated)

. 
. pwcorr weighttile kogantile kellytile, sig obs

             | weigh~le kogant~e kellyt~e
-------------+---------------------------
  weighttile |   1.0000 
             |
             |    24252
             |
   kogantile |   0.0238   1.0000 
             |   0.0205
             |     9498     9499
             |
   kellytile |   0.0814  -0.0292   1.0000 
             |   0.0000   0.0137
             |    18155     7114    18155
             |

. 
. gen topweight=(weighttile==100) if weighttile~=.
(3 missing values generated)

. gen topkogan=(kogantile==100) if kogantile~=.
(14,756 missing values generated)

. gen topkelly=(kellytile==100) if kellytile~=.
(6,100 missing values generated)

. 
. sum bank oldcapmkt consfin insur pay oldit otherind bankapp payapp otherapp us if topweight==1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        bank |        239    .0209205    .1434186          0          1
   oldcapmkt |        239    .0041841    .0646846          0          1
     consfin |        239    .0209205    .1434186          0          1
       insur |        239    .1631799    .3703053          0          1
         pay |        239    .1004184    .3011878          0          1
-------------+---------------------------------------------------------
       oldit |        239      .41841    .4943334          0          1
    otherind |        239    .2719665    .4459066          0          1
     bankapp |        239    .1757322    .3813909          0          1
      payapp |        239    .4435146    .4978418          0          1
    otherapp |        239    .4435146    .4978418          0          1
-------------+---------------------------------------------------------
          us |        239    .9372385    .2430425          0          1

. sum bank oldcapmkt consfin insur pay oldit otherind bankapp payapp otherapp us if topkogan==1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        bank |         94    .7765957    .4187605          0          1
   oldcapmkt |         94    .0425532    .2029298          0          1
     consfin |         94           0           0          0          0
       insur |         94    .0106383    .1031421          0          1
         pay |         94    .0212766    .1450787          0          1
-------------+---------------------------------------------------------
       oldit |         94           0           0          0          0
    otherind |         94    .1489362    .3579345          0          1
     bankapp |         94    .3404255    .4763931          0          1
      payapp |         94    .6170213    .4887197          0          1
    otherapp |         94    .2340426    .4256692          0          1
-------------+---------------------------------------------------------
          us |         94    .9574468    .2029298          0          1

. sum bank oldcapmkt consfin insur pay oldit otherind bankapp payapp otherapp us if topkelly==1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        bank |        180    .0611111    .2402022          0          1
   oldcapmkt |        180    .1055556     .308125          0          1
     consfin |        180    .0055556    .0745356          0          1
       insur |        180         .05    .2185529          0          1
         pay |        180    .0166667    .1283762          0          1
-------------+---------------------------------------------------------
       oldit |        180    .2611111    .4404656          0          1
    otherind |        180          .5    .5013947          0          1
     bankapp |        180    .2388889    .4275941          0          1
      payapp |        180    .3666667    .4832386          0          1
    otherapp |        180    .4444444    .4982901          0          1
-------------+---------------------------------------------------------
          us |        180    .6611111    .4746523          0          1

. tab assignee_type if topweight==1

assignee_ty |
         pe |      Freq.     Percent        Cum.
------------+-----------------------------------
          2 |        201       92.63       92.63
          3 |         15        6.91       99.54
          4 |          1        0.46      100.00
------------+-----------------------------------
      Total |        217      100.00

. tab assignee_type if topkogan==1

assignee_ty |
         pe |      Freq.     Percent        Cum.
------------+-----------------------------------
          2 |         94      100.00      100.00
------------+-----------------------------------
      Total |         94      100.00

. tab assignee_type if topkelly==1

assignee_ty |
         pe |      Freq.     Percent        Cum.
------------+-----------------------------------
          2 |         93       60.00       60.00
          3 |         56       36.13       96.13
          4 |          4        2.58       98.71
          5 |          2        1.29      100.00
------------+-----------------------------------
      Total |        155      100.00

. tab division if topweight==1

          division |      Freq.     Percent        Cum.
-------------------+-----------------------------------
East North Central |         42       18.75       18.75
   Middle Atlantic |         43       19.20       37.95
          Mountain |          4        1.79       39.73
       New England |         16        7.14       46.88
           Pacific |         73       32.59       79.46
    South Atlantic |         27       12.05       91.52
West North Central |          5        2.23       93.75
West South Central |         14        6.25      100.00
-------------------+-----------------------------------
             Total |        224      100.00

. tab division if topkogan==1

          division |      Freq.     Percent        Cum.
-------------------+-----------------------------------
East North Central |          4        4.44        4.44
   Middle Atlantic |         23       25.56       30.00
          Mountain |          3        3.33       33.33
       New England |          2        2.22       35.56
           Pacific |         24       26.67       62.22
    South Atlantic |         17       18.89       81.11
West North Central |          5        5.56       86.67
West South Central |         12       13.33      100.00
-------------------+-----------------------------------
             Total |         90      100.00

. tab division if topkelly==1

          division |      Freq.     Percent        Cum.
-------------------+-----------------------------------
East North Central |         10        8.40        8.40
East South Central |          1        0.84        9.24
   Middle Atlantic |         46       38.66       47.90
          Mountain |          3        2.52       50.42
       New England |         16       13.45       63.87
           Pacific |         17       14.29       78.15
    South Atlantic |         17       14.29       92.44
West North Central |          2        1.68       94.12
West South Central |          7        5.88      100.00
-------------------+-----------------------------------
             Total |        119      100.00

. tab company_name if topweight==1, sort

                           company_name |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
State Farm Mutual Automobile Insuranc.. |         20       10.15       10.15
                              Visa Inc. |         15        7.61       17.77
 United Services Automobile Association |         10        5.08       22.84
               The Allstate Corporation |          7        3.55       26.40
                          Dynamics Inc. |          6        3.05       29.44
           Honeywell International Inc. |          6        3.05       32.49
                           Kajeet, Inc. |          6        3.05       35.53
                        Honeywell, Inc. |          5        2.54       38.07
             Palatin Technologies, Inc. |          5        2.54       40.61
                          Alphabet Inc. |          4        2.03       42.64
                             Apple Inc. |          4        2.03       44.67
                    Progressive Corp Pa |          4        2.03       46.70
                     Sprint Corporation |          4        2.03       48.73
                     Blaze Mobile, Inc. |          3        1.52       50.25
                 First Data Corporation |          3        1.52       51.78
                        Fujitsu Limited |          3        1.52       53.30
International Business Machines Corpo.. |          3        1.52       54.82
    Intertrust Technologies Corporation |          3        1.52       56.35
                     McDATA Corporation |          3        1.52       57.87
                          QSecure, Inc. |          3        1.52       59.39
Trading Technologies International, I.. |          3        1.52       60.91
          Universal Secure Registry LLC |          3        1.52       62.44
                              AT&T Inc. |          2        1.02       63.45
                       Amazon.com, Inc. |          2        1.02       64.47
               American Express Company |          2        1.02       65.48
                               CA, Inc. |          2        1.02       66.50
         Citicorp Credit Services, Inc. |          2        1.02       67.51
                 ConsumerInfo.com, Inc. |          2        1.02       68.53
                  Cummins-Allison Corp. |          2        1.02       69.54
   Experian Information Solutions, Inc. |          2        1.02       70.56
                            Intuit Inc. |          2        1.02       71.57
                          Kofax Limited |          2        1.02       72.59
           Metrologic Instruments, Inc. |          2        1.02       73.60
                  Microsoft Corporation |          2        1.02       74.62
                         Paydiant, Inc. |          2        1.02       75.63
                       RSA Security LLC |          2        1.02       76.65
The Hartford Financial Services Group.. |          2        1.02       77.66
Toshiba Global Commerce Solutions Hol.. |          2        1.02       78.68
                              eBay Inc. |          2        1.02       79.70
                             Adobe Inc. |          1        0.51       80.20
                   Aon Holdings Limited |          1        0.51       80.71
            Bank of America Corporation |          1        0.51       81.22
                     BlackBerry Limited |          1        0.51       81.73
                       CRIF Corporation |          1        0.51       82.23
                    Cisco Systems, Inc. |          1        0.51       82.74
      Citicorp Development Center, Inc. |          1        0.51       83.25
                     Corbis Corporation |          1        0.51       83.76
                               Dell EMC |          1        0.51       84.26
               Evryx Technologies, Inc. |          1        0.51       84.77
  GE Corporate Financial Services, Inc. |          1        0.51       85.28
                      GTECH Corporation |          1        0.51       85.79
                      HSBC Holdings plc |          1        0.51       86.29
      International Game Technology PLC |          1        0.51       86.80
                   JPMorgan Chase & Co. |          1        0.51       87.31
         L-1 Secure Credentialing, Inc. |          1        0.51       87.82
                               MetaBank |          1        0.51       88.32
                    Mitek Systems, Inc. |          1        0.51       88.83
                            Mozido, LLC |          1        0.51       89.34
            NeoMedia Technologies, Inc. |          1        0.51       89.85
                 Network Merchants, LLC |          1        0.51       90.36
                      Nokia Corporation |          1        0.51       90.86
                     Oracle Corporation |          1        0.51       91.37
                  PayPal Holdings, Inc. |          1        0.51       91.88
                        Payfont Limited |          1        0.51       92.39
          Pixel Instruments Corporation |          1        0.51       92.89
                   Planet Payment, Inc. |          1        0.51       93.40
       Princeton Payment Solutions, LLC |          1        0.51       93.91
                    Saba Software, Inc. |          1        0.51       94.42
                      Sabre Corporation |          1        0.51       94.92
             Sears Holdings Corporation |          1        0.51       95.43
                      Sharp Corporation |          1        0.51       95.94
                       SimplyTapp, Inc. |          1        0.51       96.45
                           Square, Inc. |          1        0.51       96.95
      Tata Consultancy Services Limited |          1        0.51       97.46
              The Western Union Company |          1        0.51       97.97
                       Turbonomic, Inc. |          1        0.51       98.48
                           Tyfone, Inc. |          1        0.51       98.98
                           UBS Group AG |          1        0.51       99.49
                  Wells Fargo & Company |          1        0.51      100.00
----------------------------------------+-----------------------------------
                                  Total |        197      100.00

. tab company_name if topkogan==1, sort

                           company_name |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
                   JPMorgan Chase & Co. |         40       42.55       42.55
                  Wells Fargo & Company |         19       20.21       62.77
                           Walmart Inc. |         14       14.89       77.66
            Bank of America Corporation |         13       13.83       91.49
                Mastercard Incorporated |          2        2.13       93.62
                         Morgan Stanley |          2        2.13       95.74
     American International Group, Inc. |          1        1.06       96.81
  Federal National Mortgage Association |          1        1.06       97.87
      TD Ameritrade Holding Corporation |          1        1.06       98.94
          The Goldman Sachs Group, Inc. |          1        1.06      100.00
----------------------------------------+-----------------------------------
                                  Total |         94      100.00

. tab company_name if topkelly==1, sort

                           company_name |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
                           Gemalto N.V. |          6        5.36        5.36
                NXP Semiconductors N.V. |          6        5.36       10.71
                   Royal Bank of Canada |          5        4.46       15.18
                   JPMorgan Chase & Co. |          3        2.68       17.86
        New York Life Insurance Company |          3        2.68       20.54
                     Oracle Corporation |          3        2.68       23.21
 Telefonaktiebolaget LM Ericsson (publ) |          3        2.68       25.89
Trading Technologies International, I.. |          3        2.68       28.57
                   Vestek Systems, Inc. |          3        2.68       31.25
                    WMS Industries Inc. |          3        2.68       33.93
                Avalion Consulting, LLC |          2        1.79       35.71
                  Barclays Capital Inc. |          2        1.79       37.50
                     Coventry First LLC |          2        1.79       39.29
     Credit Suisse Securities (USA) LLC |          2        1.79       41.07
                      Nokia Corporation |          2        1.79       42.86
        Proton World International N.V. |          2        1.79       44.64
                 Virtu ITG Holdings LLC |          2        1.79       46.43
                AMG National Trust Bank |          1        0.89       47.32
                             AT&T Corp. |          1        0.89       48.21
                             Aetna Inc. |          1        0.89       49.11
                Alaris Holdings Limited |          1        0.89       50.00
          Alibaba Group Holding Limited |          1        0.89       50.89
               American Express Company |          1        0.89       51.79
     American International Group, Inc. |          1        0.89       52.68
                     BGC Partners, Inc. |          1        0.89       53.57
            Bank of America Corporation |          1        0.89       54.46
          Bankers Insurance Group, Inc. |          1        0.89       55.36
                         Bloomberg L.P. |          1        0.89       56.25
                   Bundesdruckerei GmbH |          1        0.89       57.14
                      CLS Services Ltd. |          1        0.89       58.04
                            Cardlab ApS |          1        0.89       58.93
                          De La Rue plc |          1        0.89       59.82
               Deloitte Development LLC |          1        0.89       60.71
           Dynamic Risk Assumption Inc. |          1        0.89       61.61
Electronics and Telecommunications Re.. |          1        0.89       62.50
        Entersekt International Limited |          1        0.89       63.39
              Evnine & Associates, Inc. |          1        0.89       64.29
                                FMR LLC |          1        0.89       65.18
                          FOLIOfn, Inc. |          1        0.89       66.07
            First Trust Portfolios L.P. |          1        0.89       66.96
                   Future Route Limited |          1        0.89       67.86
               Genworth Financial, Inc. |          1        0.89       68.75
                        H&R Block, Inc. |          1        0.89       69.64
                          Hitachi, Ltd. |          1        0.89       70.54
        Interactive Brokers Group, Inc. |          1        0.89       71.43
International Business Machines Corpo.. |          1        0.89       72.32
                    Kyocera Corporation |          1        0.89       73.21
                    Level 3 Parent, LLC |          1        0.89       74.11
           Lincoln National Corporation |          1        0.89       75.00
                       Managed ETFs LLC |          1        0.89       75.89
   Markov Processes International, Inc. |          1        0.89       76.79
                Mastercard Incorporated |          1        0.89       77.68
                        MaxLinear, Inc. |          1        0.89       78.57
                         Morgan Stanley |          1        0.89       79.46
              Mount Lucas Management LP |          1        0.89       80.36
                        NCR Corporation |          1        0.89       81.25
                        NEC Corporation |          1        0.89       82.14
                       NTT DOCOMO, INC. |          1        0.89       83.04
Nederlandse Organisatie voor toegepas.. |          1        0.89       83.93
          Net 1 UEPS Technologies, Inc. |          1        0.89       84.82
                        Ocean Tomo, LLC |          1        0.89       85.71
                  Panasonic Corporation |          1        0.89       86.61
                          Panduit Corp. |          1        0.89       87.50
                   ProFund Advisors LLC |          1        0.89       88.39
               Research Affiliates, LLC |          1        0.89       89.29
                        S&P Global Inc. |          1        0.89       90.18
           Spring Consulting Group, LLC |          1        0.89       91.07
           State Street Global Advisors |          1        0.89       91.96
         Swiss Reinsurance Company Ltd. |          1        0.89       92.86
The Guardian Life Insurance Company o.. |          1        0.89       93.75
 The PNC Financial Services Group, Inc. |          1        0.89       94.64
 United Services Automobile Association |          1        0.89       95.54
    Universal Entertainment Corporation |          1        0.89       96.43
                              Visa Inc. |          1        0.89       97.32
            Weather Risk Solutions, LLC |          1        0.89       98.21
           Wilmington Trust Corporation |          1        0.89       99.11
                        ZTE Corporation |          1        0.89      100.00
----------------------------------------+-----------------------------------
                                  Total |        112      100.00

. 
. * Table 4
. 
. ** Panel A
. 
. sort company_name

. by company_name: egen count=count(patent) 

. tab company_name if count>300, sort

                           company_name |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
            Bank of America Corporation |        652       13.09       13.09
Trading Technologies International, I.. |        645       12.95       26.04
                              Visa Inc. |        608       12.21       38.25
          Diebold Nixdorf, Incorporated |        597       11.99       50.23
International Business Machines Corpo.. |        589       11.82       62.06
                Mastercard Incorporated |        418        8.39       70.45
                   JPMorgan Chase & Co. |        407        8.17       78.62
               American Express Company |        404        8.11       86.73
 United Services Automobile Association |        351        7.05       93.78
                            Intuit Inc. |        310        6.22      100.00
----------------------------------------+-----------------------------------
                                  Total |      4,981      100.00

. 
. * Table A-6
. 
. gen sub250=(employment<250) if employment~=.
(12,082 missing values generated)

. gen sub500=(employment<500) if employment~=.
(12,082 missing values generated)

. gen sub1000=(employment<1000) if employment~=.
(12,082 missing values generated)

. by appyrearly, sort: sum sub250 sub500 sub1000

------------------------------------------------------------------------------------------------------------------------
-> appyrearly = 0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      sub250 |      9,533     .017623    .1315836          0          1
      sub500 |      9,533    .0274835     .163496          0          1
     sub1000 |      9,533    .0436379    .2042988          0          1

------------------------------------------------------------------------------------------------------------------------
-> appyrearly = 1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      sub250 |      2,640    .0238636    .1526532          0          1
      sub500 |      2,640    .0575758    .2329836          0          1
     sub1000 |      2,640    .0780303    .2682701          0          1


. by appyrlate, sort: sum sub250 sub500 sub1000

------------------------------------------------------------------------------------------------------------------------
-> appyrlate = 0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      sub250 |     10,923    .0191339     .137002          0          1
      sub500 |     10,923    .0355214     .185102          0          1
     sub1000 |     10,923    .0532821    .2246057          0          1

------------------------------------------------------------------------------------------------------------------------
-> appyrlate = 1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      sub250 |      1,250       .0176     .131545          0          1
      sub500 |      1,250       .0208    .1427714          0          1
     sub1000 |      1,250        .032    .1760704          0          1


. drop sub250 sub500 sub1000

. 
. * Table 4, Panels B, C and D
. 
. egen earlytotal=sum(appyrearly)

. egen latetotal=sum(appyrlate)

. by company_name, sort: egen countearly=sum(appyrearly) 

. by company_name: egen countlate=sum(appyrlate)

. replace countearly=0 if countearly==.
(0 real changes made)

. replace countlate=0 if countlate==.
(0 real changes made)

. gen change=(countlate/latetotal)-(countearly/earlytotal)

. bys company_name: egen meanweighted=mean(weighted)

. by company_name: egen meankogan=mean(kogan_etal_val)
(7,129 missing values generated)

. by company_name: egen meankelly=mean(kelly_etal_val_5)
(792 missing values generated)

. sort company_name

. save temp, replace
file temp.dta saved

. by company_name: drop if _n~=1
(22,045 observations deleted)

. sort change

. list company_name change in 1/11

     +---------------------------------------------------------+
     | company_name                                     change |
     |---------------------------------------------------------|
  1. |                                               -.0614867 |
  2. | First Data Corporation                          -.02435 |
  3. | The Goldman Sachs Group, Inc.                 -.0152342 |
  4. | JPMorgan Chase & Co.                          -.0140441 |
  5. | Fujitsu Limited                               -.0131403 |
     |---------------------------------------------------------|
  6. | Hitachi, Ltd.                                 -.0125761 |
  7. | HP Inc.                                        -.012388 |
  8. | International Business Machines Corporation   -.0118302 |
  9. | Oracle Corporation                            -.0103192 |
 10. | Sony Corporation                              -.0102576 |
     |---------------------------------------------------------|
 11. | Diebold Nixdorf, Incorporated                 -.0102475 |
     +---------------------------------------------------------+

. list company_name change in -11/L

      +-----------------------------------------------------------+
      | company_name                                       change |
      |-----------------------------------------------------------|
2200. | United Services Automobile Association           .0082855 |
2201. | Wells Fargo & Company                            .0087365 |
2202. | The Hartford Financial Services Group, Inc.      .0105541 |
2203. | The Allstate Corporation                         .0154557 |
2204. | Capital One Services, LLC                        .0224629 |
      |-----------------------------------------------------------|
2205. | Visa Inc.                                        .0272248 |
2206. | PayPal Holdings, Inc.                            .0305603 |
2207. | Mastercard Incorporated                          .0327407 |
2208. | State Farm Mutual Automobile Insurance Company   .0377056 |
2209. | Square, Inc.                                     .0425191 |
      |-----------------------------------------------------------|
2210. | Bank of America Corporation                      .0612704 |
      +-----------------------------------------------------------+

. drop if count<200
(2,191 observations deleted)

. gsort -meanweighted

. list company_name meanweighted in 1/3

     +---------------------------------------------------+
     | company_name                             meanwe~d |
     |---------------------------------------------------|
  1. | Square, Inc.                             3.501222 |
  2. | United Services Automobile Association     2.9958 |
  3. | Visa Inc.                                1.807734 |
     +---------------------------------------------------+

. gsort -meankogan

. list company_name meankogan in 1/3

     +----------------------------------------+
     | company_name                  meanko~n |
     |----------------------------------------|
  1. | JPMorgan Chase & Co.           266.299 |
  2. | Bank of America Corporation   108.2798 |
  3. | Visa Inc.                     107.9815 |
     +----------------------------------------+

. gsort -meankelly

. list company_name meankelly in 1/3

     +-----------------------------------+
     | company_name             meanke~y |
     |-----------------------------------|
  1. | NCR Corporation          1.090783 |
  2. | First Data Corporation   1.089851 |
  3. | Microsoft Corporation     1.05096 |
     +-----------------------------------+

. 
. ** Looking at corporate region changes
. 
. *** Setting up
. 
. use temp, clear

. by company_name app_period, sort: egen modalcsa=mode(csa_code), max
warning: For at least one group, csa_code contains all missing values. Generating missing values for the modes in
         these groups. Use option missing to treat missing values as a category.
(2,362 missing values generated)

. drop if app_period~=2015
(21,762 observations deleted)

. by company_name, sort: drop if _n~=1
(2,057 observations deleted)

. keep company_name modalcsa

. ren modalcsa latemode

. save temp2, replace
file temp2.dta saved

. use temp

. merge m:1 company_name using temp2

    Result                      Number of obs
    -----------------------------------------
    Not matched                         5,821
        from master                     5,821  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            18,434  (_merge==3)
    -----------------------------------------

. drop _merge

. save temp, replace
file temp.dta saved

. by company_name app_period, sort: egen modalcsa=mode(csa_code), max
warning: For at least one group, csa_code contains all missing values. Generating missing values for the modes in
         these groups. Use option missing to treat missing values as a category.
(2,362 missing values generated)

. drop if app_period~=2000
(18,938 observations deleted)

. by company_name, sort: drop if _n~=1
(4,395 observations deleted)

. keep company_name modalcsa

. ren modalcsa earlymode

. save temp3, replace
file temp3.dta saved

. use temp

. merge m:1 company_name using temp3

    Result                      Number of obs
    -----------------------------------------
    Not matched                         3,840
        from master                     3,840  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            20,415  (_merge==3)
    -----------------------------------------

. drop _merge

. save temp, replace
file temp.dta saved

. 
. *** Table A-16
. 
. by company_name, sort: drop if _n~=1
(22,045 observations deleted)

. drop if company_name==""
(1 observation deleted)

. 
. ***Panel A
. 
. sum count countearly countlate

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       count |      2,209    8.484382     39.8975          1        652
  countearly |      2,209    1.814848    8.596355          0        193
   countlate |      2,209    .9203259    6.294622          0        164

. sum count countearly if countearly>0 & countlate==0 

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       count |        792    4.893939    11.61787          1        183
  countearly |        792    2.314394     4.53428          1         81

. sum count countlate if countlate>0 & countearly==0 

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       count |        306     6.19281    18.94389          1        259
   countlate |        306     2.79085    8.765172          1        106

. sum count countearly countlate if (countearly>0 & countlate>0)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       count |        129    85.47287    138.9893          2        652
  countearly |        129    16.86822    29.74248          1        193
   countlate |        129    9.139535    20.30346          1        164

. sum count countearly countlate if ((countearly>0 & countlate>0) & (earlymode~=. & latemode~=.) & (earlymode==latemode)
> )

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       count |         41     116.878    164.1119          2        645
  countearly |         41    17.90244    25.97961          1        127
   countlate |         41    11.36585    18.01632          1         81

. sum count countearly countlate if ((countearly>0 & countlate>0) & (earlymode~=. & latemode~=.) & (earlymode~=latemode)
> )

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       count |         28         130    191.7556          3        652
  countearly |         28    26.07143    47.03421          1        193
   countlate |         28    15.92857    35.35841          1        164

. 
. *** Panel B
. 
. tab earlymode if ((countearly>0 & countlate>0) & (earlymode~=. & latemode~=.) & (earlymode~=latemode)), sum(count)

            |          Summary of count
  earlymode |        Mean   Std. dev.       Freq.
------------+------------------------------------
        122 |        15.5   .70710678           2
        147 |           4           0           1
        148 |          35           0           1
        168 |          45           0           1
        176 |          10           0           1
        216 |         297           0           1
        268 |          31           0           1
        348 |           3           0           1
        370 |          11           0           1
        408 |   308.66667    246.5431           9
        422 |          19           0           1
        440 |          71           0           1
        488 |   62.666667   60.484158           3
        500 |          16           0           1
        548 |   33.666667   21.779195           3
------------+------------------------------------
      Total |         130   191.75563          28

. tab latemode if ((countearly>0 & countlate>0) & (earlymode~=. & latemode~=.) & (earlymode~=latemode)), sum(count)

            |          Summary of count
   latemode |        Mean   Std. dev.       Freq.
------------+------------------------------------
        122 |         297           0           1
        148 |          12           0           1
        172 |         652           0           1
        176 |          16           0           1
        184 |          16           0           1
        206 |          19           0           1
        278 |         259           0           1
        332 |           3           0           1
        370 |         404           0           1
        378 |         131           0           1
        408 |          29   21.130547           5
        420 |          27           0           1
        428 |         407           0           1
        450 |   24.666667   14.571662           3
        462 |         589           0           1
        476 |         418           0           1
        488 |   16.333333   12.503333           3
        500 |          71           0           1
        518 |          10           0           1
        548 |          41           0           1
------------+------------------------------------
      Total |         130   191.75563          28

. 
. gen switch=0 if ((countearly>0 & countlate>0))
(2,080 missing values generated)

. replace switch=1 if ((countearly>0 & countlate>0) & (earlymode~=. & latemode~=.) & (earlymode!=latemode))
(28 real changes made)

. 
. gen NYearly=(earlymode==408)

. gen SFearly=(earlymode==488)

. 
. gen Sum2000FinVC=117.94 if earlymode==122
(2,188 missing values generated)

. replace Sum2000FinVC= 233.92 if earlymode==148
(25 real changes made)

. replace Sum2000FinVC= 74.09 if earlymode==176
(30 real changes made)

. replace Sum2000FinVC= 0.62 if earlymode==194
(1 real change made)

. replace Sum2000FinVC= 0.10 if earlymode==198
(2 real changes made)

. replace Sum2000FinVC= 561.22 if earlymode==206
(24 real changes made)

. replace Sum2000FinVC= 600.00 if earlymode==216
(12 real changes made)

. replace Sum2000FinVC= 100.25 if earlymode==220
(8 real changes made)

. replace Sum2000FinVC= 1.68 if earlymode==294
(0 real changes made)

. replace Sum2000FinVC= 0.10 if earlymode==300
(0 real changes made)

. replace Sum2000FinVC= 6.00 if earlymode==312
(10 real changes made)

. replace Sum2000FinVC= 16.00 if earlymode==336
(0 real changes made)

. replace Sum2000FinVC= 41.86 if earlymode==348
(30 real changes made)

. replace Sum2000FinVC= 54.06 if earlymode==370
(12 real changes made)

. replace Sum2000FinVC= 0.50 if earlymode==400
(0 real changes made)

. replace Sum2000FinVC= 4.00 if earlymode==406
(1 real change made)

. replace Sum2000FinVC= 232.70 if earlymode==408
(110 real changes made)

. replace Sum2000FinVC= 6.00 if earlymode==412
(0 real changes made)

. replace Sum2000FinVC= 15.00 if earlymode==416
(2 real changes made)

. replace Sum2000FinVC= 16.00 if earlymode==422
(2 real changes made)

. replace Sum2000FinVC= 3.74 if earlymode==426
(1 real change made)

. replace Sum2000FinVC= 36.00 if earlymode==428
(17 real changes made)

. replace Sum2000FinVC= 74.70 if earlymode==430
(6 real changes made)

. replace Sum2000FinVC= 0.11 if earlymode==440
(9 real changes made)

. replace Sum2000FinVC= 0.50 if earlymode==450
(8 real changes made)

. replace Sum2000FinVC= 4.30 if earlymode==476
(3 real changes made)

. replace Sum2000FinVC= 19.50 if earlymode==482
(8 real changes made)

. replace Sum2000FinVC= 1107.68 if earlymode==488
(116 real changes made)

. replace Sum2000FinVC= 30.45 if earlymode==500
(20 real changes made)

. replace Sum2000FinVC= 0.80 if earlymode==545
(1 real change made)

. replace Sum2000FinVC= 0 if Sum2000FinVC==.
(1,730 real changes made)

. 
. ** Table A-22
. 
. probit switch bank capmkt it vc_backed public if ((countearly>0 & countlate>0)) [weight=countearly], vce(r)
(frequency weights assumed)

Iteration 0:  Log pseudolikelihood =  -1388.267  
Iteration 1:  Log pseudolikelihood = -1196.9951  
Iteration 2:  Log pseudolikelihood = -1196.1646  
Iteration 3:  Log pseudolikelihood = -1196.1646  

Probit regression                                       Number of obs =  2,176
                                                        Wald chi2(5)  = 360.41
                                                        Prob > chi2   = 0.0000
Log pseudolikelihood = -1196.1646                       Pseudo R2     = 0.1384

------------------------------------------------------------------------------
             |               Robust
      switch | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |   .7109044   .1524955     4.66   0.000     .4120187     1.00979
      capmkt |  -.1282975   .1264995    -1.01   0.310     -.376232    .1196369
          it |  -1.023542   .0918571   -11.14   0.000    -1.203579   -.8435056
   vc_backed |  -.4638446   .4879404    -0.95   0.342     -1.42019    .4925011
      public |  -.2204491   .0733618    -3.00   0.003    -.3642355   -.0766627
       _cons |   .4322431   .0798901     5.41   0.000     .2756613    .5888248
------------------------------------------------------------------------------

. probit switch bank capmkt it vc_backed public NYearly SFearly if ((countearly>0 & countlate>0)) [weight=countearly], v
> ce(r)
(frequency weights assumed)

Iteration 0:  Log pseudolikelihood =  -1388.267  
Iteration 1:  Log pseudolikelihood = -850.29029  
Iteration 2:  Log pseudolikelihood = -842.60831  
Iteration 3:  Log pseudolikelihood = -842.58626  
Iteration 4:  Log pseudolikelihood = -842.58626  

Probit regression                                      Number of obs =   2,176
                                                       Wald chi2(7)  = 1055.85
                                                       Prob > chi2   =  0.0000
Log pseudolikelihood = -842.58626                      Pseudo R2     =  0.3931

------------------------------------------------------------------------------
             |               Robust
      switch | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |   -.399017   .1320197    -3.02   0.003    -.6577709   -.1402631
      capmkt |  -1.337409   .1465572    -9.13   0.000    -1.624656   -1.050162
          it |  -1.377779   .0966613   -14.25   0.000    -1.567232   -1.188327
   vc_backed |  -.2328637   .5497666    -0.42   0.672    -1.310386    .8446591
      public |  -.5657489   .1034854    -5.47   0.000    -.7685766   -.3629213
     NYearly |   2.128622   .0977086    21.79   0.000     1.937116    2.320127
     SFearly |   .2031207   .1021469     1.99   0.047     .0029165    .4033249
       _cons |   .4427352   .0830495     5.33   0.000     .2799611    .6055093
------------------------------------------------------------------------------

. probit switch bank capmkt it vc_backed public NYearly SFearly Sum2000FinVC if ((countearly>0 & countlate>0)) [weight=c
> ountearly], vce(r)
(frequency weights assumed)

Iteration 0:  Log pseudolikelihood =  -1388.267  
Iteration 1:  Log pseudolikelihood = -824.27093  
Iteration 2:  Log pseudolikelihood =  -815.5824  
Iteration 3:  Log pseudolikelihood = -815.55906  
Iteration 4:  Log pseudolikelihood = -815.55906  

Probit regression                                      Number of obs =   2,176
                                                       Wald chi2(8)  = 1058.85
                                                       Prob > chi2   =  0.0000
Log pseudolikelihood = -815.55906                      Pseudo R2     =  0.4125

------------------------------------------------------------------------------
             |               Robust
      switch | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
        bank |   .3025802   .1397862     2.16   0.030     .0286042    .5765562
      capmkt |  -.6444675   .1576728    -4.09   0.000    -.9535005   -.3354345
          it |  -.6910335   .1057966    -6.53   0.000     -.898391    -.483676
   vc_backed |   .2669487   .4710832     0.57   0.571    -.6563575    1.190255
      public |  -.4948026   .1090341    -4.54   0.000    -.7085054   -.2810998
     NYearly |   1.830844   .0992291    18.45   0.000     1.636359     2.02533
     SFearly |  -1.800279   .2191325    -8.22   0.000    -2.229771   -1.370787
Sum2000FinVC |    .002025   .0002171     9.33   0.000     .0015996    .0024504
       _cons |  -.4735961   .1297009    -3.65   0.000    -.7278051   -.2193871
------------------------------------------------------------------------------

. 
. 
. 
. *** CORPVC.TXT
. 
. * This analysis is used to generate Figure 2 only
. 
. * Clearing vars
. clear

. 
. * Gatherng data
. 
. import excel using "Corporate VC into Finance Firms All Data", sheet("Deals") first
(19 vars, 11,908 obs)

. keep oid AllTransactionsAnnouncedDate TotalTransactionValueUSDmm

. gen year=year(AllTransactionsAnnouncedDate)

. drop AllTransactionsAnnouncedDate

. gen period=1 if year<=2004 & year>=2000
(10,585 missing values generated)

. replace period=2 if year>2004 & year<=2009
(2,175 real changes made)

. replace period=3 if year>2009 & year<=2014
(3,416 real changes made)

. replace period=4 if year>2014 & year<=2019
(4,994 real changes made)

. save temp, replace
file temp.dta saved

. clear

. import excel using "Corporate VC into Finance Firms All Data", sheet("Investor Company Details") first
(344 vars, 11,908 obs)

. reshape long BuyersInvestors IQ_id_ Company_Type_ Company_Country_ Ultimate_Parent_Name_ Ultimate_Parent_IQ_ID_, i(oid
>  CIQTransactionID) j(id)
(j = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 4
> 2 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations           11,908   ->   678,756     
Number of variables                 344   ->   9           
j variable (57 values)                    ->   id
xij variables:
BuyersInvestors1 BuyersInvestors2 ... BuyersInvestors57->BuyersInvestors
           IQ_id_1 IQ_id_2 ... IQ_id_57   ->   IQ_id_
Company_Type_1 Company_Type_2 ... Company_Type_57->Company_Type_
Company_Country_1 Company_Country_2 ... Company_Country_57->Company_Country_
Ultimate_Parent_Name_1 Ultimate_Parent_Name_2 ... Ultimate_Parent_Name_57->Ultimate_Parent_Name_
Ultimate_Parent_IQ_ID_1 Ultimate_Parent_IQ_ID_2 ... Ultimate_Parent_IQ_ID_57->Ultimate_Parent_IQ_ID_
-----------------------------------------------------------------------------

. drop if BuyersInvestors==""
(655,810 observations deleted)

. sort oid

. by oid: egen maxcount=max(id)

. keep oid id BuyersInvestors IQ_id_ Company_Type_ Company_Country_ maxcount

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
         oid |     22,946    6088.008    3486.944          1      11908
          id |     22,946     2.38717    2.929687          1         57
BuyersInve~s |          0
      IQ_id_ |          0
Company_Ty~_ |          0
-------------+---------------------------------------------------------
Company_Co~_ |          0
    maxcount |     22,946     3.77434    4.736838          1         57

. merge m:1 oid using temp

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                            22,946  (_merge==3)
    -----------------------------------------

. save temp, replace
file temp.dta saved

. clear

. import excel using "Corporate VC into Finance Firms All Data", sheet("Investor Industry Details") first
(12 vars, 9,030 obs)

. keep BuyerInvestorCapIQID BuyerInvestorUltimateParent BuyerInvestorUPIndustryGroup BuyerInvestorUPPrimaryIndust

. ren BuyerInvestorCapIQID IQ_id_

. sort IQ_id_

. by IQ_id_: drop if _n~=1
(28 observations deleted)

. save temp2, replace
file temp2.dta saved

. use temp

. drop _merge

. merge m:1 IQ_id_ using temp2
(variable IQ_id_ was str11, now str12 to accommodate using data's values)

    Result                      Number of obs
    -----------------------------------------
    Not matched                             9
        from master                         6  (_merge==1)
        from using                          3  (_merge==2)

    Matched                            22,940  (_merge==3)
    -----------------------------------------

. drop _merge

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
         oid |     22,946    6088.008    3486.944          1      11908
          id |     22,946     2.38717    2.929687          1         57
BuyersInve~s |          0
      IQ_id_ |          0
Company_Ty~_ |          0
-------------+---------------------------------------------------------
Company_Co~_ |          0
    maxcount |     22,946     3.77434    4.736838          1         57
TotalTrans~m |     19,260    120.1552    707.0404          0   40999.09
        year |     22,946    2012.361    5.795315       2000       2019
      period |     22,946    3.057919    1.075045          1          4
-------------+---------------------------------------------------------
BuyerInve~nt |          0
BuyerInves~p |          0
BuyerInve~st |          0

. tab Company_Type_

                    Company_Type_ |      Freq.     Percent        Cum.
----------------------------------+-----------------------------------
             (Invalid Identifier) |          1        0.00        0.00
                  Assets/Products |          1        0.00        0.01
         Corporate Investment Arm |      1,021        4.49        4.50
          Educational Institution |          5        0.02        4.52
 Financial Service Investment Arm |      1,572        6.91       11.43
Foundation/Charitable Institution |         32        0.14       11.57
           Government Institution |        581        2.55       14.12
                  Private Company |      3,213       14.12       28.25
                     Private Fund |         79        0.35       28.59
          Private Investment Firm |     13,000       57.15       85.74
                   Public Company |      2,549       11.20       96.94
                      Public Fund |        194        0.85       97.80
           Public Investment Firm |        500        2.20      100.00
                Trade Association |          1        0.00      100.00
----------------------------------+-----------------------------------
                            Total |     22,749      100.00

. 
. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Citi Ventures, Inc."
(13 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="CommerzVentures"
(12 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Neva Finventures Sgr"
(6 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Allianz Digital Corporate Ventures"
(6 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Allianz X GmbH"
(5 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="NAventures"
(4 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Wachovia Strategic Ventures Group"
(4 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Aviva Ventures"
(3 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="DB1 Ventures GmbH"
(3 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="Liberty Mutual Strategic Ventures"
(3 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="MS&AD Ventures Inc."
(3 real changes made)

. replace Company_Type_="Corporate Investment Arm" if BuyersInvestors=="MUFG Innovation Partners Co., Ltd."
(4 real changes made)

. replace Company_Type_="Financial Service Investment Arm" if BuyersInvestors=="Oakwood Global Finance LLP"
(1 real change made)

. fre BuyersInv if Company_Type_=="Corporate Investment Arm", all width(100) desc

BuyersInvestors
--------------------------------------------------------------------------------------------------------------------
                                                                       |      Freq.    Percent      Valid       Cum.
-----------------------------------------------------------------------+--------------------------------------------
Valid   Intel Capital                                                  |         34       3.13       3.13       3.13
        GV                                                             |         32       2.95       2.95       6.08
        Enterprise Ireland, Investment Arm                             |         22       2.03       2.03       8.10
        GMO VenturePartners, Inc.                                      |         20       1.84       1.84       9.94
        Triodos Investment Management BV                               |         14       1.29       1.29      11.23
        Citi Ventures, Inc.                                            |         13       1.20       1.20      12.43
        Comcast Ventures                                               |         13       1.20       1.20      13.63
        Octopus Investments Limited                                    |         13       1.20       1.20      14.83
        American Express Ventures                                      |         12       1.10       1.10      15.93
        CommerzVentures                                                |         12       1.10       1.10      17.03
        Fenway Summer Ventures                                         |         12       1.10       1.10      18.14
        Horizons Ventures Limited                                      |         12       1.10       1.10      19.24
        PROPARCO SA                                                    |         12       1.10       1.10      20.35
        Salesforce Ventures, Inc.                                      |         12       1.10       1.10      21.45
        Transamerica Ventures, LLC                                     |         12       1.10       1.10      22.56
        Internet Initiatives Development Fund Invest                   |         11       1.01       1.01      23.57
        NXTP Labs S.R.L.                                               |         11       1.01       1.01      24.59
        Tencent Holdings Ltd., Investment Arm                          |         11       1.01       1.01      25.60
        Ben Franklin Technology Partners of Southeastern Pennsylvania, |          9       0.83       0.83      26.43
        Investment Arm                                                 |                                            
        Endeavor Global, Inc., Investment Arm                          |          9       0.83       0.83      27.26
        Legend Capital Management Co., Ltd.                            |          9       0.83       0.83      28.08
        Cisco Investments                                              |          8       0.74       0.74      28.82
        Kapor Capital                                                  |          8       0.74       0.74      29.56
        MDI Ventures                                                   |          8       0.74       0.74      30.29
        SoftBank Investment Advisers (UK) Limited                      |          8       0.74       0.74      31.03
        Fosun RZ Venture Management Co., Ltd.                          |          7       0.64       0.64      31.68
        Globis Capital Partners                                        |          7       0.64       0.64      32.32
        Rakuten, Inc., Investment Arm                                  |          7       0.64       0.64      32.97
        Recruit Strategic Partners, Inc.                               |          7       0.64       0.64      33.61
        Allianz Digital Corporate Ventures                             |          6       0.55       0.55      34.16
        CME Ventures LLC                                               |          6       0.55       0.55      34.71
        Capital Enterprise, Investment Arm                             |          6       0.55       0.55      35.27
        Dentsu Innovation Partners Inc.                                |          6       0.55       0.55      35.82
        Metropolitan Partners Group                                    |          6       0.55       0.55      36.37
        Neva Finventures Sgr                                           |          6       0.55       0.55      36.92
        Novel TMT Ventures Limited                                     |          6       0.55       0.55      37.48
        Orange Capital SA                                              |          6       0.55       0.55      38.03
        The Scottish Investment Bank                                   |          6       0.55       0.55      38.58
        Vulcan Capital                                                 |          6       0.55       0.55      39.13
        Wayra Investigación y Desarrollo, S.L.U.                       |          6       0.55       0.55      39.69
        XL Innovate, LLC                                               |          6       0.55       0.55      40.24
        Allianz X GmbH                                                 |          5       0.46       0.46      40.70
        Beedie Capital                                                 |          5       0.46       0.46      41.16
        Bertelsmann India Investments                                  |          5       0.46       0.46      41.62
        Bertelsmann Management (Shanghai) Co., Ltd, Beijing Branch     |          5       0.46       0.46      42.08
        Bloomberg Beta L.P.                                            |          5       0.46       0.46      42.54
        CapitalG Management Company, LLC                               |          5       0.46       0.46      43.00
        Dieter von Holtzbrinck Ventures GmbH                           |          5       0.46       0.46      43.46
        First Data Corp. Internet Ventures                             |          5       0.46       0.46      43.92
        Fortress Investment Group LLC                                  |          5       0.46       0.46      44.38
        Kickstart Ventures                                             |          5       0.46       0.46      44.84
        LINE Ventures Corporation                                      |          5       0.46       0.46      45.30
        M12                                                            |          5       0.46       0.46      45.76
        Pamodzi Investment Holdings                                    |          5       0.46       0.46      46.22
        ProSiebenSat.1 Accelerator                                     |          5       0.46       0.46      46.69
        Project A Ventures GmbH & Co. KG                               |          5       0.46       0.46      47.15
        QUALCOMM Ventures                                              |          5       0.46       0.46      47.61
        SoftBank Capital                                               |          5       0.46       0.46      48.07
        Tengelmann Ventures Management GmbH                            |          5       0.46       0.46      48.53
        The National Digital Research Centre Limited, Investment Arm   |          5       0.46       0.46      48.99
        UPS Strategic Enterprise Fund                                  |          5       0.46       0.46      49.45
        ALLVP                                                          |          4       0.37       0.37      49.82
        Astarc Ventures                                                |          4       0.37       0.37      50.18
        Brand Capital                                                  |          4       0.37       0.37      50.55
        Dell Ventures                                                  |          4       0.37       0.37      50.92
        Flare Capital Management Company, LLC                          |          4       0.37       0.37      51.29
        Fosun Capital                                                  |          4       0.37       0.37      51.66
        Gradient Ventures                                              |          4       0.37       0.37      52.03
        MUFG Innovation Partners Co., Ltd.                             |          4       0.37       0.37      52.39
        MasterCard Start Path                                          |          4       0.37       0.37      52.76
        Monex Ventures Co., Ltd.                                       |          4       0.37       0.37      53.13
        Montagu Private Equity LLP                                     |          4       0.37       0.37      53.50
        Munich Re/HSB Ventures                                         |          4       0.37       0.37      53.87
        NAventures                                                     |          4       0.37       0.37      54.24
        New York City Investment Fund Manager, Inc.                    |          4       0.37       0.37      54.60
        Prosus Ventures                                                |          4       0.37       0.37      54.97
        REV Venture Partners Limited                                   |          4       0.37       0.37      55.34
        SGInnovate                                                     |          4       0.37       0.37      55.71
        SevenVentures GmbH                                             |          4       0.37       0.37      56.08
        Sinar Mas Digital Ventures                                     |          4       0.37       0.37      56.45
        TVS Capital Funds Limited                                      |          4       0.37       0.37      56.81
        Thomson Financial Ventures                                     |          4       0.37       0.37      57.18
        Tracxn Labs                                                    |          4       0.37       0.37      57.55
        VCET Capital Corporation                                       |          4       0.37       0.37      57.92
        Wachovia Strategic Ventures Group                              |          4       0.37       0.37      58.29
        Wamda Capital                                                  |          4       0.37       0.37      58.66
        YJ Capital Inc.                                                |          4       0.37       0.37      59.02
        Adobe Ventures                                                 |          3       0.28       0.28      59.30
        Ascalon Capital Managers Limited                               |          3       0.28       0.28      59.58
        Aviva Ventures                                                 |          3       0.28       0.28      59.85
        CIT GAP Funds                                                  |          3       0.28       0.28      60.13
        Captii Ventures Pte. Ltd.                                      |          3       0.28       0.28      60.41
        Cargill Financial Services International Inc.                  |          3       0.28       0.28      60.68
        Coinbase, Inc., Investment Arm                                 |          3       0.28       0.28      60.96
        DB1 Ventures GmbH                                              |          3       0.28       0.28      61.23
        Dublin Business Innovation Centre, Investment Arm              |          3       0.28       0.28      61.51
        EDB Investments Pte. Ltd.                                      |          3       0.28       0.28      61.79
        ESW Capital, LLC                                               |          3       0.28       0.28      62.06
        Formula Ventures Ltd.                                          |          3       0.28       0.28      62.34
        Gray Matters Capital, Endowment Arm                            |          3       0.28       0.28      62.62
        InMotion Ventures Ltd.                                         |          3       0.28       0.28      62.89
        J.F. Shea Venture Capital                                      |          3       0.28       0.28      63.17
        Koch Ventures, Inc.                                            |          3       0.28       0.28      63.44
        Liberty Mutual Strategic Ventures                              |          3       0.28       0.28      63.72
        MS&AD Ventures Inc.                                            |          3       0.28       0.28      64.00
        Manvest Inc.                                                   |          3       0.28       0.28      64.27
        Multicultural Innovation Lab                                   |          3       0.28       0.28      64.55
        Nationwide Mutual Capital                                      |          3       0.28       0.28      64.83
        Nesta Investment Management LLP                                |          3       0.28       0.28      65.10
        Performance Equity Management, LLC                             |          3       0.28       0.28      65.38
        Principia SGR                                                  |          3       0.28       0.28      65.65
        STRIVE                                                         |          3       0.28       0.28      65.93
        Samsung Venture Investment Corporation                         |          3       0.28       0.28      66.21
        Swisscom Ventures                                              |          3       0.28       0.28      66.48
        TLabs                                                          |          3       0.28       0.28      66.76
        Telstra Ventures Pty. Limited                                  |          3       0.28       0.28      67.03
        The North West Fund                                            |          3       0.28       0.28      67.31
        Voyage Ventures, Inc.                                          |          3       0.28       0.28      67.59
        WDB Investment Holdings Pty Ltd.                               |          3       0.28       0.28      67.86
        Aditya Birla Private Equity                                    |          2       0.18       0.18      68.05
        Aerospace Science & Industry Asset Management Co., Ltd.        |          2       0.18       0.18      68.23
        Aga Khan Fund for Economic Development                         |          2       0.18       0.18      68.42
        Anschutz Investment Company                                    |          2       0.18       0.18      68.60
        Axel Springer Digital Ventures GmbH                            |          2       0.18       0.18      68.78
        CyberAgent Capital Co., Ltd.                                   |          2       0.18       0.18      68.97
        DMG Information                                                |          2       0.18       0.18      69.15
        Deutsche Telekom Strategic Investments GmbH                    |          2       0.18       0.18      69.34
        Dubai International Capital L.L.C.                             |          2       0.18       0.18      69.52
        Eastman Ventures                                               |          2       0.18       0.18      69.71
        Equinor Technology Invest                                      |          2       0.18       0.18      69.89
        Foresight Group LLP                                            |          2       0.18       0.18      70.07
        GemVentures                                                    |          2       0.18       0.18      70.26
        Gestión de Capital Riesgo del País Vasco, SGEIC, S.A.          |          2       0.18       0.18      70.44
        Great White Shark Enterprises, Inc, Investment Arm             |          2       0.18       0.18      70.63
        Gunosy Capital Pte. Ltd.                                       |          2       0.18       0.18      70.81
        HDFC Private Equity                                            |          2       0.18       0.18      70.99
        Hearst Ventures                                                |          2       0.18       0.18      71.18
        ITOCHU Technology Ventures, Inc.                               |          2       0.18       0.18      71.36
        International Business Machines Corp., Investment Arm          |          2       0.18       0.18      71.55
        Investitionsbank Berlin, Investment Arm                        |          2       0.18       0.18      71.73
        JD Capital Co., Ltd.                                           |          2       0.18       0.18      71.92
        Japan Post Capital Co., Ltd.                                   |          2       0.18       0.18      72.10
        Legend Star                                                    |          2       0.18       0.18      72.28
        Lunds Universitets Innovationssystem AB                        |          2       0.18       0.18      72.47
        MAIF Avenir SAS                                                |          2       0.18       0.18      72.65
        McCarthy Partners Management, LLC                              |          2       0.18       0.18      72.84
        Medici Ventures, Inc.                                          |          2       0.18       0.18      73.02
        Mitsui & Co. Global Investment, Inc.                           |          2       0.18       0.18      73.20
        Motorola Solutions Venture Capital                             |          2       0.18       0.18      73.39
        NFP Ventures                                                   |          2       0.18       0.18      73.57
        NOM Finance                                                    |          2       0.18       0.18      73.76
        Netease Capital                                                |          2       0.18       0.18      73.94
        North-East Venture A/S                                         |          2       0.18       0.18      74.13
        O.G. Tech Ventures                                             |          2       0.18       0.18      74.31
        Ona Capital Privat, SCR de R.S., S.A.                          |          2       0.18       0.18      74.49
        Opt Ventures Co, Ltd.                                          |          2       0.18       0.18      74.68
        Presidio STX, LLC                                              |          2       0.18       0.18      74.86
        Rakuten Ventures                                               |          2       0.18       0.18      75.05
        Recruit Holdings Co.,Ltd., Investment Arm                      |          2       0.18       0.18      75.23
        Reliance Technology Ventures Limited                           |          2       0.18       0.18      75.41
        Schibsted Growth                                               |          2       0.18       0.18      75.60
        Sesame Ventures                                                |          2       0.18       0.18      75.78
        Shanghai Yonghua Capital Management Co., Ltd.                  |          2       0.18       0.18      75.97
        Singapore Angel Network Pte. Ltd                               |          2       0.18       0.18      76.15
        Singtel Innov8 Pte. Ltd.                                       |          2       0.18       0.18      76.34
        Sistema Venture Capital                                        |          2       0.18       0.18      76.52
        Smilegate Investment, Inc.                                     |          2       0.18       0.18      76.70
        Softbank China & India Holdings                                |          2       0.18       0.18      76.89
        Sony Innovation Fund                                           |          2       0.18       0.18      77.07
        Spiral Ventures Pte Ltd                                        |          2       0.18       0.18      77.26
        Sprout Venture Partners                                        |          2       0.18       0.18      77.44
        State Auto Labs Corp.                                          |          2       0.18       0.18      77.62
        Sumitomo Corporation Equity Asia Limited                       |          2       0.18       0.18      77.81
        T5 Equity Partners, LLC                                        |          2       0.18       0.18      77.99
        Verizon Ventures                                               |          2       0.18       0.18      78.18
        Vorwerk Direct Selling Ventures GmbH                           |          2       0.18       0.18      78.36
        WS Investments                                                 |          2       0.18       0.18      78.55
        WarnerMedia Investments                                        |          2       0.18       0.18      78.73
        Wipro Ventures Ltd                                             |          2       0.18       0.18      78.91
        Work-Bench Ventures                                            |          2       0.18       0.18      79.10
        Zhuhai Huachuang Investment Management Co., Ltd.               |          2       0.18       0.18      79.28
        muru-D                                                         |          2       0.18       0.18      79.47
        3M New Ventures                                                |          1       0.09       0.09      79.56
        @Ventures                                                      |          1       0.09       0.09      79.65
        A2F Consulting LLC, Investment Arm                             |          1       0.09       0.09      79.74
        AE Ventures                                                    |          1       0.09       0.09      79.83
        AGNC Ventures, LLC                                             |          1       0.09       0.09      79.93
        AL Arif Investments LLC                                        |          1       0.09       0.09      80.02
        AOL Ventures                                                   |          1       0.09       0.09      80.11
        Accelerasia, Investment Arm                                    |          1       0.09       0.09      80.20
        Admitad Invest                                                 |          1       0.09       0.09      80.29
        Air Liquide Investissements d'Avenir et de Demonstration S.A.  |          1       0.09       0.09      80.39
        Air Liquide Ventures                                           |          1       0.09       0.09      80.48
        Amazon.com Inc., Investment Arm                                |          1       0.09       0.09      80.57
        Amgen Ventures                                                 |          1       0.09       0.09      80.66
        Ann Arbor SPARK, Investment Arm                                |          1       0.09       0.09      80.76
        Aquila Infrastructure Management Inc.                          |          1       0.09       0.09      80.85
        Arizona Bay Technology Ventures                                |          1       0.09       0.09      80.94
        Arnela Capital Privado, S.C.R., S.A.                           |          1       0.09       0.09      81.03
        Arrive                                                         |          1       0.09       0.09      81.12
        Artificial Life Investments Ltd.                               |          1       0.09       0.09      81.22
        Arzan Venture Capital                                          |          1       0.09       0.09      81.31
        Ascension Ventures                                             |          1       0.09       0.09      81.40
        Avista Ventures, Inc.                                          |          1       0.09       0.09      81.49
        Axiata Group Berhad, Investment Arm                            |          1       0.09       0.09      81.58
        B2B Infrastructure Investment Fund                             |          1       0.09       0.09      81.68
        BAMS Angels Fund                                               |          1       0.09       0.09      81.77
        BP Ventures Limited                                            |          1       0.09       0.09      81.86
        BRAINWORKS Capital Management (Private) Limited                |          1       0.09       0.09      81.95
        BXA Ventures                                                   |          1       0.09       0.09      82.04
        Baidu, Inc., Investment Arm                                    |          1       0.09       0.09      82.14
        Banif Capital - Sociedade de Capital de Risco S.A.             |          1       0.09       0.09      82.23
        Beenos Partners                                                |          1       0.09       0.09      82.32
        Bertelsmann Digital Media Investments Inc.                     |          1       0.09       0.09      82.41
        BitFury Capital                                                |          1       0.09       0.09      82.50
        Blackbirch Capital Inc., Investment Arm                        |          1       0.09       0.09      82.60
        BlueCross BlueShield Venture Partners, L.P.                    |          1       0.09       0.09      82.69
        Boehringer Ingelheim, Investment Arm                           |          1       0.09       0.09      82.78
        Bokwang Investment Corporation                                 |          1       0.09       0.09      82.87
        Bonsai Venture Capital SA SCR                                  |          1       0.09       0.09      82.97
        Bouygues Telecom Initiatives                                   |          1       0.09       0.09      83.06
        Business Leaders For Michigan, Investment Arm                  |          1       0.09       0.09      83.15
        CAA Ventures                                                   |          1       0.09       0.09      83.24
        Cambridge Innovations                                          |          1       0.09       0.09      83.33
        Caterpillar Ventures                                           |          1       0.09       0.09      83.43
        China Merchants Technology Holdings Co., Ltd.                  |          1       0.09       0.09      83.52
        CincyTechUSA, Investment Arm                                   |          1       0.09       0.09      83.61
        Clal Industries and Investments Ltd., Investment Arm           |          1       0.09       0.09      83.70
        CommIT, LLC                                                    |          1       0.09       0.09      83.79
        Cyberworks Ventures                                            |          1       0.09       0.09      83.89
        DMG Information Asia Pacific                                   |          1       0.09       0.09      83.98
        DOEN Participaties BV                                          |          1       0.09       0.09      84.07
        Danone Communities                                             |          1       0.09       0.09      84.16
        DeNA Venture Capital Group                                     |          1       0.09       0.09      84.25
        DoCoMo Capital, Inc.                                           |          1       0.09       0.09      84.35
        Dowling & Partners Securities, LLC, Investment Arm             |          1       0.09       0.09      84.44
        Downey Ventures                                                |          1       0.09       0.09      84.53
        Dunamu & Partners                                              |          1       0.09       0.09      84.62
        Edenred Capital Partners                                       |          1       0.09       0.09      84.71
        Empresa Nacional de Innovación, SME, S.A.                      |          1       0.09       0.09      84.81
        Engineers Without Borders Canada, Endowment Arm                |          1       0.09       0.09      84.90
        Equinor Energy Ventures                                        |          1       0.09       0.09      84.99
        Evergy Ventures                                                |          1       0.09       0.09      85.08
        Evonik Venture Capital GmbH                                    |          1       0.09       0.09      85.17
        FSE Fund Managers Limited                                      |          1       0.09       0.09      85.27
        Fifth Street Capital LLC                                       |          1       0.09       0.09      85.36
        Freebit Investment Co., Ltd.                                   |          1       0.09       0.09      85.45
        Fuchsia Venture Capital                                        |          1       0.09       0.09      85.54
        Fuji Startup Ventures Inc.                                     |          1       0.09       0.09      85.64
        Fundepar Gestão De Investimentos Ltda.                         |          1       0.09       0.09      85.73
        GC1 Ventures                                                   |          1       0.09       0.09      85.82
        GO Ventures LLC                                                |          1       0.09       0.09      85.91
        General Motors Ventures, LLC                                   |          1       0.09       0.09      86.00
        Generator Ventures                                             |          1       0.09       0.09      86.10
        German Ventures GmbH                                           |          1       0.09       0.09      86.19
        Gibraltar Ventures, LLC                                        |          1       0.09       0.09      86.28
        Gordon Brothers Europe                                         |          1       0.09       0.09      86.37
        HCM Capital                                                    |          1       0.09       0.09      86.46
        Hamilton Venture Capital Ltd, Investment Arm                   |          1       0.09       0.09      86.56
        HardGamma Ventures                                             |          1       0.09       0.09      86.65
        Hi Inov SAS                                                    |          1       0.09       0.09      86.74
        High Impact Capital Advisors Ltd., Investment Arm              |          1       0.09       0.09      86.83
        Hollinger Capital                                              |          1       0.09       0.09      86.92
        Hong Kong Cyberport Management Company Limited, Investment Arm |          1       0.09       0.09      87.02
        Hyield Venture Capital Co., Ltd.                               |          1       0.09       0.09      87.11
        IBERDROLA Ventures-PERSEO                                      |          1       0.09       0.09      87.20
        IDB Investments                                                |          1       0.09       0.09      87.29
        IDC Venture Capital                                            |          1       0.09       0.09      87.38
        INTRO Invest GmbH                                              |          1       0.09       0.09      87.48
        InVent Venture Capital                                         |          1       0.09       0.09      87.57
        InVivo Invest                                                  |          1       0.09       0.09      87.66
        Incutex S.A.                                                   |          1       0.09       0.09      87.75
        Infineon Ventures GmbH                                         |          1       0.09       0.09      87.85
        Ingenico Ventures SAS                                          |          1       0.09       0.09      87.94
        Initiative IP                                                  |          1       0.09       0.09      88.03
        Isetan Mitsukoshi Innovations                                  |          1       0.09       0.09      88.12
        Itochu Finance Corp.                                           |          1       0.09       0.09      88.21
        JetBlue Technology Ventures                                    |          1       0.09       0.09      88.31
        Jiangsu Tech industry Investment Corp.                         |          1       0.09       0.09      88.40
        Jiangyin Huaxicun Investment Co., Ltd.                         |          1       0.09       0.09      88.49
        Juniper Networks, Investment Arm                               |          1       0.09       0.09      88.58
        KPC Energy Ventures, Inc.                                      |          1       0.09       0.09      88.67
        Kalonia Venture Partners                                       |          1       0.09       0.09      88.77
        Kirnaf Finance Company                                         |          1       0.09       0.09      88.86
        Knight Foundation, Investment Arm                              |          1       0.09       0.09      88.95
        Le B612 Participations, SAS                                    |          1       0.09       0.09      89.04
        Lhasa Bainian Dehua Investment Co., Ltd.                       |          1       0.09       0.09      89.13
        Liberate Corporate Venture Fund                                |          1       0.09       0.09      89.23
        Liberty Israel Venture Fund, LLC                               |          1       0.09       0.09      89.32
        MGEN Tech Fund                                                 |          1       0.09       0.09      89.41
        MaRs Discovery District, Investment Arm                        |          1       0.09       0.09      89.50
        Mad'a Investment Company                                       |          1       0.09       0.09      89.59
        Maotian Capital Company Limited                                |          1       0.09       0.09      89.69
        Masdar Venture Capital                                         |          1       0.09       0.09      89.78
        MediaTek Ventures                                              |          1       0.09       0.09      89.87
        Medtronic Asset Management, Inc.                               |          1       0.09       0.09      89.96
        Meltwater Entrepreneurial School of Technology, Investment Arm |          1       0.09       0.09      90.06
        Mercado Libre's Venture Capital Fund                           |          1       0.09       0.09      90.15
        MetLife Digital Ventures                                       |          1       0.09       0.09      90.24
        Metropole Nice Cote D'azur, Endowment Arm                      |          1       0.09       0.09      90.33
        Millicom International Cellular SA, Investment Arm             |          1       0.09       0.09      90.42
        Mitsui Private Equity                                          |          1       0.09       0.09      90.52
        NHN Investment Co., Ltd.                                       |          1       0.09       0.09      90.61
        NTT Docomo Ventures, Inc.                                      |          1       0.09       0.09      90.70
        Nasdaq Ventures                                                |          1       0.09       0.09      90.79
        Nem SGR S.p.A.                                                 |          1       0.09       0.09      90.88
        Next47 GmbH                                                    |          1       0.09       0.09      90.98
        Nippon Life Global Investors Americas, Inc.                    |          1       0.09       0.09      91.07
        Noah Holdings Limited, Investment Arm                          |          1       0.09       0.09      91.16
        Nogle Capital Management                                       |          1       0.09       0.09      91.25
        North Industries Group Investment Management Company Ltd.      |          1       0.09       0.09      91.34
        Novo Holdings A/S                                              |          1       0.09       0.09      91.44
        OCI Venture Group                                              |          1       0.09       0.09      91.53
        Oltre Venture                                                  |          1       0.09       0.09      91.62
        Omnivore Partners                                              |          1       0.09       0.09      91.71
        One97 Communications Limited, Investment Arm                   |          1       0.09       0.09      91.80
        Oracle Ventures                                                |          1       0.09       0.09      91.90
        Orange Fab                                                     |          1       0.09       0.09      91.99
        Orchestra Investment Inc.                                      |          1       0.09       0.09      92.08
        PICC Capital Investment Management Co. Ltd                     |          1       0.09       0.09      92.17
        PSG Alpha                                                      |          1       0.09       0.09      92.27
        Pacific Mercantile Bank, Investment Arm                        |          1       0.09       0.09      92.36
        Panda Capital Management Co., Ltd.                             |          1       0.09       0.09      92.45
        Paragon Bank, Investment Arm                                   |          1       0.09       0.09      92.54
        Raise Ventures                                                 |          1       0.09       0.09      92.63
        Reaktor Ventures                                               |          1       0.09       0.09      92.73
        Reliance Venture Asset Management Private Limited              |          1       0.09       0.09      92.82
        Residex Venture Capital Network                                |          1       0.09       0.09      92.91
        Rev1 Ventures, Investment Arm                                  |          1       0.09       0.09      93.00
        Robert Bosch Venture Capital GmbH                              |          1       0.09       0.09      93.09
        SAIC Capital Company Limited                                   |          1       0.09       0.09      93.19
        SEED Venture Finance, LLC                                      |          1       0.09       0.09      93.28
        SGAM AG2R La Mondiale, Investment Arm                          |          1       0.09       0.09      93.37
        SIX FinTech Ventures                                           |          1       0.09       0.09      93.46
        SKT Ventures                                                   |          1       0.09       0.09      93.55
        Safaricom Limited, Investment Arm                              |          1       0.09       0.09      93.65
        Saison Capital Pte. Ltd.                                       |          1       0.09       0.09      93.74
        Saison Ventures Co., Ltd.                                      |          1       0.09       0.09      93.83
        Samsung America Venture Capital Company                        |          1       0.09       0.09      93.92
        Samsung NEXT                                                   |          1       0.09       0.09      94.01
        Scient Capital                                                 |          1       0.09       0.09      94.11
        Shanghai Daofeng Investment Co. Ltd                            |          1       0.09       0.09      94.20
        Shanghai International Group Assets Management Co., Ltd.       |          1       0.09       0.09      94.29
        Shell Ventures                                                 |          1       0.09       0.09      94.38
        Shizuoka Capital Company Limited                               |          1       0.09       0.09      94.48
        Showcase Capital Co., Ltd.                                     |          1       0.09       0.09      94.57
        Siemens Venture Capital GmbH                                   |          1       0.09       0.09      94.66
        Slack Technologies, Inc., Investment Arm                       |          1       0.09       0.09      94.75
        Sofiouest SA                                                   |          1       0.09       0.09      94.84
        SoftBank Ventures Asia                                         |          1       0.09       0.09      94.94
        Softline Venture Partners                                      |          1       0.09       0.09      95.03
        Sonera Venture Capital                                         |          1       0.09       0.09      95.12
        Southeast University Education Foundation, Endowment Arm       |          1       0.09       0.09      95.21
        SpareBank 1 SMN, Investment Arm                                |          1       0.09       0.09      95.30
        Sphere Private Equity                                          |          1       0.09       0.09      95.40
        Steamboat Ventures, LLC                                        |          1       0.09       0.09      95.49
        Strada Education Network, Endownment Arm                       |          1       0.09       0.09      95.58
        Suez Asia Holdings Pte. Ltd.                                   |          1       0.09       0.09      95.67
        Sun Microsystems Venture & Strategic Investments               |          1       0.09       0.09      95.76
        Supply Chain Angels                                            |          1       0.09       0.09      95.86
        Suzhou Haihui Investment Co., Ltd.                             |          1       0.09       0.09      95.95
        Symantec Ventures                                              |          1       0.09       0.09      96.04
        Syngenta Ventures                                              |          1       0.09       0.09      96.13
        TBS Innovation Partners LLC                                    |          1       0.09       0.09      96.22
        TI Ventures                                                    |          1       0.09       0.09      96.32
        TIM Ventures                                                   |          1       0.09       0.09      96.41
        Taipei Fubon Commercial Bank Co., Ltd., Investment Arm         |          1       0.09       0.09      96.50
        The Benaroya Company, Investment Arm                           |          1       0.09       0.09      96.59
        The Innovation Group                                           |          1       0.09       0.09      96.69
        The Next 36, Endowment Arm                                     |          1       0.09       0.09      96.78
        The University of Tokyo Edge Capital Co., Ltd.                 |          1       0.09       0.09      96.87
        The Whittemore Collection Ltd.                                 |          1       0.09       0.09      96.96
        Three Gorges Capital Holdings Co., Ltd.                        |          1       0.09       0.09      97.05
        Tianjin Tasly Pharmaceutical Co., Ltd., Investment Arm         |          1       0.09       0.09      97.15
        Tibet Gongbo gyamda Jiusheng Investment Co., Ltd.              |          1       0.09       0.09      97.24
        Tongfang Financial Holding (Shenzhen) Co., Ltd.                |          1       0.09       0.09      97.33
        Tongfang Financial Holdings (Shenzhen) Co., Ltd.               |          1       0.09       0.09      97.42
        Total Carbon Neutrality Ventures                               |          1       0.09       0.09      97.51
        Transcosmos Investments & Business Development, Inc.           |          1       0.09       0.09      97.61
        UNIQA Ventures GmbH                                            |          1       0.09       0.09      97.70
        UTokyo Innovation Platform Co., Ltd.                           |          1       0.09       0.09      97.79
        UniCredit Bank AG, Investment Arm                              |          1       0.09       0.09      97.88
        Vectren Enterprises, Inc.                                      |          1       0.09       0.09      97.97
        VentureTech Alliance LLC                                       |          1       0.09       0.09      98.07
        Verein Innovationsfonds                                        |          1       0.09       0.09      98.16
        Virgin Green Fund                                              |          1       0.09       0.09      98.25
        Vodafone Ventures                                              |          1       0.09       0.09      98.34
        Volvo Group Venture Capital AB                                 |          1       0.09       0.09      98.43
        Wooshin Venture Investment Corp.                               |          1       0.09       0.09      98.53
        Wuhan Economic Development and Investment Group Co., Ltd,      |          1       0.09       0.09      98.62
        Investment Arm                                                 |                                            
        XTX Ventures                                                   |          1       0.09       0.09      98.71
        Xiamen CCRE Investment Co., Ltd.                               |          1       0.09       0.09      98.80
        Xiaomi Ventures Limited                                        |          1       0.09       0.09      98.90
        Xpring                                                         |          1       0.09       0.09      98.99
        YeahMobi Information Technology Co., Ltd., Investment Arm      |          1       0.09       0.09      99.08
        Yicun Capital Co., Ltd.                                        |          1       0.09       0.09      99.17
        ZTE Capital Management Co., Ltd.                               |          1       0.09       0.09      99.26
        Zhejiang Baoxiniao Venture Capital Co., Ltd                    |          1       0.09       0.09      99.36
        divine InterVentures                                           |          1       0.09       0.09      99.45
        e-partners                                                     |          1       0.09       0.09      99.54
        i Mercury Capital                                              |          1       0.09       0.09      99.63
        iD TechVentures Inc.                                           |          1       0.09       0.09      99.72
        iSigma Capital Corporation                                     |          1       0.09       0.09      99.82
        iXL Ventures                                                   |          1       0.09       0.09      99.91
        nChain Reaction Ltd                                            |          1       0.09       0.09     100.00
        Total                                                          |       1086     100.00     100.00           
--------------------------------------------------------------------------------------------------------------------

. fre BuyersInv if Company_Type_=="Financial Service Investment Arm", all width(100) desc

BuyersInvestors
-----------------------------------------------------------------------------------------------------------------------
                                                                          |      Freq.    Percent      Valid       Cum.
--------------------------------------------------------------------------+--------------------------------------------
Valid   International Finance Corporation                                 |        242      16.03      16.03      16.03
        The European Bank for Reconstruction and Development, Investment  |         41       2.72       2.72      18.74
        Arm                                                               |                                            
        Norwest Venture Partners                                          |         34       2.25       2.25      20.99
        DEG-Deutsche Investitions- und Entwicklungsgesellschaft mbH       |         30       1.99       1.99      22.98
        SBI Investment Co., Ltd.                                          |         26       1.72       1.72      24.70
        TTV Capital                                                       |         25       1.66       1.66      26.36
        Santander UK Group Holdings plc, Investment Arm                   |         20       1.32       1.32      27.68
        Silicon Valley BancVentures, Inc.                                 |         20       1.32       1.32      29.01
        SIDBI Venture Capital Limited                                     |         16       1.06       1.06      30.07
        Creditease Corp., Investment Arm                                  |         15       0.99       0.99      31.06
        GE Equity                                                         |         15       0.99       0.99      32.05
        CIBC Capital Partners                                             |         12       0.79       0.79      32.85
        European Investment Fund                                          |         12       0.79       0.79      33.64
        JPMP Capital, LLC                                                 |         12       0.79       0.79      34.44
        Mizuho Capital Co., Ltd.                                          |         12       0.79       0.79      35.23
        Advans Group                                                      |         11       0.73       0.73      35.96
        Deutsche Bank AG, Investment Arm                                  |         11       0.73       0.73      36.69
        SMBC Venture Capital Co., Ltd.                                    |         11       0.73       0.73      37.42
        SVB Silicon Valley Bank, Investment Arm                           |         11       0.73       0.73      38.15
        American Family Ventures                                          |         10       0.66       0.66      38.81
        KfW, Investment Arm                                               |         10       0.66       0.66      39.47
        Lehman Brothers Private Equity Advisers LLC                       |         10       0.66       0.66      40.13
        Unitus Investment Management                                      |         10       0.66       0.66      40.79
        Broadhaven Capital Partners, LLC, Investment Arm                  |          9       0.60       0.60      41.39
        Mitsui Sumitomo Insurance Venture Capital Co., Ltd.               |          9       0.60       0.60      41.99
        Standard Chartered Private Equity Limited                         |          9       0.60       0.60      42.58
        BlueOrchard Investments Sàrl                                      |          8       0.53       0.53      43.11
        Edgewater Services, LLC                                           |          8       0.53       0.53      43.64
        GAWA Capital Partners SL                                          |          8       0.53       0.53      44.17
        Merrill Lynch Global Private Equity                               |          8       0.53       0.53      44.70
        Merrill Lynch Ventures, LLC                                       |          8       0.53       0.53      45.23
        Susquehanna Growth Equity, LLC                                    |          8       0.53       0.53      45.76
        Wavemaker Partners                                                |          8       0.53       0.53      46.29
        Accenture Technology Ventures                                     |          7       0.46       0.46      46.75
        CMFG Ventures, LLC                                                |          7       0.46       0.46      47.22
        ICICI Venture Funds Management Company Limited                    |          7       0.46       0.46      47.68
        IDB Lab                                                           |          7       0.46       0.46      48.15
        Maj Invest Equity A/S                                             |          7       0.46       0.46      48.61
        Jefferies Group, Inc., Investment Arm                             |          6       0.40       0.40      49.01
        MassMutual Ventures LLC                                           |          6       0.40       0.40      49.40
        Ping An Ventures                                                  |          6       0.40       0.40      49.80
        Reinventure Group Pty. Ltd.                                       |          6       0.40       0.40      50.20
        UBS Investment Bank, Investment Arm                               |          6       0.40       0.40      50.60
        AXA Venture Partners                                              |          5       0.33       0.33      50.93
        Arkéa Capital, SAS                                                |          5       0.33       0.33      51.26
        BNPP Capital Partners                                             |          5       0.33       0.33      51.59
        British Business Bank Investments Ltd.                            |          5       0.33       0.33      51.92
        CLSA Capital Partners                                             |          5       0.33       0.33      52.25
        DBJ Capital Co., Ltd.                                             |          5       0.33       0.33      52.58
        Haitong Capital Co., Ltd.                                         |          5       0.33       0.33      52.91
        Investec Private Equity                                           |          5       0.33       0.33      53.25
        SBI Holdings, Inc., Investment Arm                                |          5       0.33       0.33      53.58
        SIG Asia Investments, LLLP                                        |          5       0.33       0.33      53.91
        Scotiabank Private Equity Investments                             |          5       0.33       0.33      54.24
        Swiss Re Alternative Assets, LLC                                  |          5       0.33       0.33      54.57
        ABN AMRO Group N.V., Investment Arm                               |          4       0.26       0.26      54.83
        BBVA Ventures                                                     |          4       0.26       0.26      55.10
        BNDES Participações S.A. - BNDESPAR                               |          4       0.26       0.26      55.36
        BNP Paribas Développement SA, SCR                                 |          4       0.26       0.26      55.63
        Bank of China Group Investment Limited                            |          4       0.26       0.26      55.89
        Berliner Volksbank Ventures                                       |          4       0.26       0.26      56.16
        C&B Capital, L.P.                                                 |          4       0.26       0.26      56.42
        CITIC Capital Partners                                            |          4       0.26       0.26      56.69
        CITIC Private Equity Funds Management Co., Ltd.                   |          4       0.26       0.26      56.95
        CK Corporación Kutxa, S.L.                                        |          4       0.26       0.26      57.22
        Caisse des Dépôts et Consignations, Investment Arm                |          4       0.26       0.26      57.48
        Commerce Street Capital, Investment Arm                           |          4       0.26       0.26      57.75
        EdgeStone Partners, Inc.                                          |          4       0.26       0.26      58.01
        Global Capital Management Ltd.                                    |          4       0.26       0.26      58.28
        IDFC Private Equity                                               |          4       0.26       0.26      58.54
        KB Investment Co., Ltd.                                           |          4       0.26       0.26      58.81
        Kuwait Finance House, Investment Arm                              |          4       0.26       0.26      59.07
        Moelis Capital Partners LLC                                       |          4       0.26       0.26      59.34
        Opportunity Private Equity Gestora de Recursos Ltda.              |          4       0.26       0.26      59.60
        Sarona Asset Management Inc.                                      |          4       0.26       0.26      59.87
        Sinolink Securities Co., Ltd., Investment Arm                     |          4       0.26       0.26      60.13
        WR Hambrecht + Co, Investment Arm                                 |          4       0.26       0.26      60.40
        Wells Fargo & Company, Investment Arm                             |          4       0.26       0.26      60.66
        Wells Fargo Equity Capital, Inc.                                  |          4       0.26       0.26      60.93
        ABANCA Corporación Industrial y Empresarial, S.L.                 |          3       0.20       0.20      61.13
        African Development Bank, Investment Arm                          |          3       0.20       0.20      61.32
        Allen & Company Inc., Investment Arm                              |          3       0.20       0.20      61.52
        Axis Private Equity Ltd.                                          |          3       0.20       0.20      61.72
        BMO Capital Partners                                              |          3       0.20       0.20      61.92
        Banco Pastor Investment Arm                                       |          3       0.20       0.20      62.12
        Bangkok Bank Public Co. Ltd., Investment Arm                      |          3       0.20       0.20      62.32
        Bank of Scotland Equity Investments                               |          3       0.20       0.20      62.52
        BayBG                                                             |          3       0.20       0.20      62.72
        Bayern Kapital GmbH                                               |          3       0.20       0.20      62.91
        Capital Trust Limited                                             |          3       0.20       0.20      63.11
        China Development Bank Capital Corporation Ltd                    |          3       0.20       0.20      63.31
        China Everbright Investment and Assets Management Co., Ltd.       |          3       0.20       0.20      63.51
        Fifth Third Capital Holdings, LLC                                 |          3       0.20       0.20      63.71
        FundersClub Inc., Investment Arm                                  |          3       0.20       0.20      63.91
        Grail Partners, LLC, Investment Arm                               |          3       0.20       0.20      64.11
        Grupo de Negocios Duero S.A.U.                                    |          3       0.20       0.20      64.30
        Hovde Private Equity Advisors LLC                                 |          3       0.20       0.20      64.50
        Islamic Corporation for the Development of the Private Sector,    |          3       0.20       0.20      64.70
        Investment Arm                                                    |                                            
        Islamic Development Bank, Investment Arm                          |          3       0.20       0.20      64.90
        JadeValue Fintech                                                 |          3       0.20       0.20      65.10
        Korea Investment & Securities Co., Ltd., Investment Arm           |          3       0.20       0.20      65.30
        MOPE Investment Advisors Private Limited                          |          3       0.20       0.20      65.50
        Macquarie Group Limited, Investment Arm                           |          3       0.20       0.20      65.70
        National Australia Bank, Investment Arm                           |          3       0.20       0.20      65.89
        Natixis Private Equity                                            |          3       0.20       0.20      66.09
        NeSBIC Groep BV                                                   |          3       0.20       0.20      66.29
        Outcome Capital, LLC, Investment Arm                              |          3       0.20       0.20      66.49
        Russian Direct Investment Fund                                    |          3       0.20       0.20      66.69
        SBI Ven Capital Pte. Ltd.                                         |          3       0.20       0.20      66.89
        SBI-HIKARI P.E. Co., Ltd.                                         |          3       0.20       0.20      67.09
        SBT Venture Capital                                               |          3       0.20       0.20      67.28
        SEB Venture Capital                                               |          3       0.20       0.20      67.48
        Schroder Finance Partners                                         |          3       0.20       0.20      67.68
        Shinsei Bank Ltd., Investment Arm                                 |          3       0.20       0.20      67.88
        Sodero Gestion                                                    |          3       0.20       0.20      68.08
        St. Paul Venture Capital, Inc.                                    |          3       0.20       0.20      68.28
        Stonehenge Growth Capital, LLC                                    |          3       0.20       0.20      68.48
        SunTrust Equity Funding, LLC                                      |          3       0.20       0.20      68.68
        Taishin Venture Capital Co., Ltd.                                 |          3       0.20       0.20      68.87
        Tata Capital Private Equity                                       |          3       0.20       0.20      69.07
        Tianfeng Tianrui Investment Co., Ltd.                             |          3       0.20       0.20      69.27
        Windsor Private Capital Limited Partnership                       |          3       0.20       0.20      69.47
        Woori Bank Co., Ltd., Investment Arm                              |          3       0.20       0.20      69.67
        Zero2IPO Ventures                                                 |          3       0.20       0.20      69.87
        AIB Equity                                                        |          2       0.13       0.13      70.00
        Alexander Hutton Venture Partners                                 |          2       0.13       0.13      70.13
        Allianz Capital Partners GmbH                                     |          2       0.13       0.13      70.26
        Allianz Specialized Investments Limited                           |          2       0.13       0.13      70.40
        Angel Ventures Mexico L.P.                                        |          2       0.13       0.13      70.53
        Aura Funds Management Pty Ltd                                     |          2       0.13       0.13      70.66
        BM H Beteiligungs-Managementgesellschaft Hessen mbH               |          2       0.13       0.13      70.79
        BMO Equity Partners LP                                            |          2       0.13       0.13      70.93
        BNP Paribas Fortis Private Equity                                 |          2       0.13       0.13      71.06
        BOC International Holdings Ltd., Investment Arm                   |          2       0.13       0.13      71.19
        BOS Ventures LLC                                                  |          2       0.13       0.13      71.32
        BancBoston Ventures, Inc.                                         |          2       0.13       0.13      71.46
        Banco Santander, S.A., Investment Arm                             |          2       0.13       0.13      71.59
        Bank of Changsha Co., Ltd., Investment Arm                        |          2       0.13       0.13      71.72
        Bankinter Capital Riesgo, SGEIC, S.A.                             |          2       0.13       0.13      71.85
        Beacon Venture Capital Co., Ltd.                                  |          2       0.13       0.13      71.99
        Benson Oak Ventures                                               |          2       0.13       0.13      72.12
        Bohai Industrial Investment Fund Management Co., Ltd.             |          2       0.13       0.13      72.25
        Bridge Partners, Investment Arm                                   |          2       0.13       0.13      72.38
        CICC Jia Cheng Investment Management Company Limited              |          2       0.13       0.13      72.52
        Caja de Burgos Venture Capital, SCR-Pyme, S.A.                    |          2       0.13       0.13      72.65
        Capital Management House, Private Equity                          |          2       0.13       0.13      72.78
        Catalyst Fund                                                     |          2       0.13       0.13      72.91
        Changjiang Growth Capital Investment Co., Ltd.                    |          2       0.13       0.13      73.05
        Chase H&Q, Investment Arm                                         |          2       0.13       0.13      73.18
        Collector Ventures KB                                             |          2       0.13       0.13      73.31
        Credit Agricole Indosuez Acquisition Finance                      |          2       0.13       0.13      73.44
        DBS Capital Investments Ltd.                                      |          2       0.13       0.13      73.58
        Dain Rauscher Wessels, Investment Arm                             |          2       0.13       0.13      73.71
        Discount Capital                                                  |          2       0.13       0.13      73.84
        Dongxing Securities Co., Ltd., Investment Arm                     |          2       0.13       0.13      73.97
        Donnelly Penman Capital LLC                                       |          2       0.13       0.13      74.11
        Dubai Investments Co. PJSC, Investment Arm                        |          2       0.13       0.13      74.24
        Emigrant Partners                                                 |          2       0.13       0.13      74.37
        Emprise Capital Corp., Investment Arm                             |          2       0.13       0.13      74.50
        Entrepreneurs Fund Management LLP                                 |          2       0.13       0.13      74.64
        FinVentures UK Limited                                            |          2       0.13       0.13      74.77
        Fubon Financial Holding Venture Capital Co., Ltd.                 |          2       0.13       0.13      74.90
        GF Xinde Investment Management Co., Ltd                           |          2       0.13       0.13      75.03
        GP Bullhound LLP, Investment Arm                                  |          2       0.13       0.13      75.17
        Gazprombank Open Joint Stock Company, Investment Arm              |          2       0.13       0.13      75.30
        HSBC Bank plc, Investment Arm                                     |          2       0.13       0.13      75.43
        HSBC Principal Investments                                        |          2       0.13       0.13      75.56
        Huaan Securities Co., Ltd., Investment Arm                        |          2       0.13       0.13      75.70
        IBK Capital Corporation                                           |          2       0.13       0.13      75.83
        ICC Venture Capital                                               |          2       0.13       0.13      75.96
        ING Ventures                                                      |          2       0.13       0.13      76.09
        Irwin Ventures LLC                                                |          2       0.13       0.13      76.23
        Jefferies LLC, Investment Arm                                     |          2       0.13       0.13      76.36
        KBW Capital Partners                                              |          2       0.13       0.13      76.49
        Katalyst Ventures Partners                                        |          2       0.13       0.13      76.62
        Key Venture Partners                                              |          2       0.13       0.13      76.75
        Krungsri Finovate                                                 |          2       0.13       0.13      76.89
        Leumi Partners Ltd.                                               |          2       0.13       0.13      77.02
        MMP International                                                 |          2       0.13       0.13      77.15
        Macquarie Bank Limited, Investment Arm                            |          2       0.13       0.13      77.28
        Main Incubator GmbH                                               |          2       0.13       0.13      77.42
        Mandiri Capital                                                   |          2       0.13       0.13      77.55
        Mirae Asset Capital Co,Ltd., Investment Arm                       |          2       0.13       0.13      77.68
        Morgan Stanley & Co. LLC, Investment Arm                          |          2       0.13       0.13      77.81
        Mutua Madrileña Inmobiliaria                                      |          2       0.13       0.13      77.95
        NEX Opportunities                                                 |          2       0.13       0.13      78.08
        NH Investment & Securities Co., Ltd., Investment Arm              |          2       0.13       0.13      78.21
        Nationwide Building Society, Investment Arm                       |          2       0.13       0.13      78.34
        Nissay Capital Co.,Ltd                                            |          2       0.13       0.13      78.48
        Nomura Holding America, Investment Arm                            |          2       0.13       0.13      78.61
        North Pacific Bank, Ltd., Investment Arm                          |          2       0.13       0.13      78.74
        OKB Capital Co., Ltd.                                             |          2       0.13       0.13      78.87
        Ping An Capital Co., Ltd.                                         |          2       0.13       0.13      79.01
        PriceLab                                                          |          2       0.13       0.13      79.14
        Proctor NBF Capital Partners                                      |          2       0.13       0.13      79.27
        RBC Capital Partners                                              |          2       0.13       0.13      79.40
        Rabo Frontier Ventures B.V.                                       |          2       0.13       0.13      79.54
        Resona Capital Co., Ltd.                                          |          2       0.13       0.13      79.67
        SOFTBANK Europe Ventures                                          |          2       0.13       0.13      79.80
        Stephens Capital Partners LLC                                     |          2       0.13       0.13      79.93
        Sumitomo Mitsui Banking Corp., Investment Arm                     |          2       0.13       0.13      80.07
        Sumitomo Mitsui Trust Bank, Limited, Investment Arm               |          2       0.13       0.13      80.20
        The Bank of Kyoto, Ltd., Investment Arm                           |          2       0.13       0.13      80.33
        The Musashino Bank, Investment Arm                                |          2       0.13       0.13      80.46
        TriplePoint Ventures                                              |          2       0.13       0.13      80.60
        Unicredit S.P.A., Investment Arm                                  |          2       0.13       0.13      80.73
        VCDE Venture Partners Geschäftsführungs-GmbH                      |          2       0.13       0.13      80.86
        VTB Capital, Private Equity and Special Situations                |          2       0.13       0.13      80.99
        responsAbility Social Investment Services, Private Equity Arm     |          2       0.13       0.13      81.13
        A&M Capital Advisors, LLC                                         |          1       0.07       0.07      81.19
        ABC International (China) Investment Co. Ltd                      |          1       0.07       0.07      81.26
        ANZ Capital                                                       |          1       0.07       0.07      81.32
        AWI Ventures Limited                                              |          1       0.07       0.07      81.39
        Abn Amro Capital Ltd                                              |          1       0.07       0.07      81.46
        Affärsstrategerna AB                                              |          1       0.07       0.07      81.52
        Aflac Corporate Ventures                                          |          1       0.07       0.07      81.59
        Aizawa Investments Co., Ltd.                                      |          1       0.07       0.07      81.66
        Allegra Finance, Investment Arm                                   |          1       0.07       0.07      81.72
        Allen & Buckeridge Investment Management                          |          1       0.07       0.07      81.79
        Allianz Venture Partners GmbH                                     |          1       0.07       0.07      81.85
        Allied Irish Banks, p.l.c., Investment Arm                        |          1       0.07       0.07      81.92
        Almi Invest AB                                                    |          1       0.07       0.07      81.99
        Almi Invest Mitt AB                                               |          1       0.07       0.07      82.05
        Alpes Capital Innovation SAS, SCR                                 |          1       0.07       0.07      82.12
        Ambit Pragma Ventures Pvt. Ltd.                                   |          1       0.07       0.07      82.19
        American Securities LLC                                           |          1       0.07       0.07      82.25
        Aozora Investment Co., Ltd.                                       |          1       0.07       0.07      82.32
        Arpwood Partners                                                  |          1       0.07       0.07      82.38
        Aryaman Financial Services Limited, Investment Arm                |          1       0.07       0.07      82.45
        Asia Plus Group Holdings Public Company Limited, Investment Arm   |          1       0.07       0.07      82.52
        Australia & New Zealand Banking Group Limited, Investment Arm     |          1       0.07       0.07      82.58
        Avanta Ventures                                                   |          1       0.07       0.07      82.65
        Avendus Capital Private Limited, Investment Arm                   |          1       0.07       0.07      82.72
        BBH Capital Partners                                              |          1       0.07       0.07      82.78
        BES Management Limited                                            |          1       0.07       0.07      82.85
        BFB Brandenburg Kapital GmbH                                      |          1       0.07       0.07      82.91
        BHC Middle Market Funding, L.P.                                   |          1       0.07       0.07      82.98
        BIA Digital Partners LP                                           |          1       0.07       0.07      83.05
        BNK Securities Co., Ltd., Investment Arm                          |          1       0.07       0.07      83.11
        BNP Paribas E&C Capital - Americas                                |          1       0.07       0.07      83.18
        BNP Paribas e-Cube                                                |          1       0.07       0.07      83.25
        BPE Partners                                                      |          1       0.07       0.07      83.31
        BStartup 10 S.L.U.                                                |          1       0.07       0.07      83.38
        BTG Pactual Chile S.A. Corredores de Bolsa, Investment Arm        |          1       0.07       0.07      83.44
        BZ Bank, Investment Arm                                           |          1       0.07       0.07      83.51
        Banco Votorantim S.A., Investment Arm                             |          1       0.07       0.07      83.58
        Bank Hapoalim BM, Investment Management Arm                       |          1       0.07       0.07      83.64
        Bank VTB 24, Investment Arm                                       |          1       0.07       0.07      83.71
        Bank of Beijing Co., Ltd., Investment Arm                         |          1       0.07       0.07      83.77
        Banque Martin Maurel, Investment Arm                              |          1       0.07       0.07      83.84
        Barclays Principal Investments Limited                            |          1       0.07       0.07      83.91
        Belmont Partners LLC, Investment Arm                              |          1       0.07       0.07      83.97
        BitMEX Ventures                                                   |          1       0.07       0.07      84.04
        Blom Bank, Investment Arm                                         |          1       0.07       0.07      84.11
        BlueOrchard Finance S.A., Asset Management Arm                    |          1       0.07       0.07      84.17
        Broadview Capital Partners                                        |          1       0.07       0.07      84.24
        CA Capital, Sociedade de Capital de Risco, SA                     |          1       0.07       0.07      84.30
        CDIB Capital International (Hong Kong) Corporation Limited        |          1       0.07       0.07      84.37
        CEA Capital Corp., Investment Arm                                 |          1       0.07       0.07      84.44
        CICC Investment Group Company Limited                             |          1       0.07       0.07      84.50
        CITIC Capital Holdings Limited, Investment Arm                    |          1       0.07       0.07      84.57
        CLR Private Equity, Prior to Change in Line of Business           |          1       0.07       0.07      84.64
        CMS Small-Cap Private Equity Fund                                 |          1       0.07       0.07      84.70
        Caitong Securities Co., Ltd., Investment Arm                      |          1       0.07       0.07      84.77
        CaixaBank, S.A., Investment Arm                                   |          1       0.07       0.07      84.83
        Canapi Ventures                                                   |          1       0.07       0.07      84.90
        Capital One Ventures                                              |          1       0.07       0.07      84.97
        Capital Riesgo Internet S.C.R, S.A - BSCH                         |          1       0.07       0.07      85.03
        Cascadia Capital Partners                                         |          1       0.07       0.07      85.10
        CatalunyaCaixa Capital, S.A.                                      |          1       0.07       0.07      85.17
        Cathay Venture Inc.                                               |          1       0.07       0.07      85.23
        Cazenove Private Equity                                           |          1       0.07       0.07      85.30
        Chardan Capital Markets LLC, Investment Arm                       |          1       0.07       0.07      85.36
        Chibagin Capital Co., Ltd.                                        |          1       0.07       0.07      85.43
        China Development Financial Holding Corporation, Investment Arm   |          1       0.07       0.07      85.50
        China Great Wall Securities Co., Ltd., Investment Arm             |          1       0.07       0.07      85.56
        Citigroup Capital UK Limited                                      |          1       0.07       0.07      85.63
        Company Guides Venture Partners                                   |          1       0.07       0.07      85.70
        Corigin Private Equity Group                                      |          1       0.07       0.07      85.76
        CorporacciónCan - Grupo Corporativo Empresarial Caja Navara       |          1       0.07       0.07      85.83
        Cotyledon Capital Inc.                                            |          1       0.07       0.07      85.89
        Cowen Capital Partners, LLC                                       |          1       0.07       0.07      85.96
        Credit Suisse Entrepreneur Capital AG                             |          1       0.07       0.07      86.03
        Credit Suisse Entrepreneur Capital Ltd.                           |          1       0.07       0.07      86.09
        Credit Suisse Group, Investment Arm                               |          1       0.07       0.07      86.16
        Credito Valtellinese Societa Cooperativa, Investment Arm          |          1       0.07       0.07      86.23
        Crédit Agricole PG Développement                                  |          1       0.07       0.07      86.29
        DB Investment Partners, Inc.                                      |          1       0.07       0.07      86.36
        Daiwa Securities SMBC Principal Investments Co. Ltd.              |          1       0.07       0.07      86.42
        Dalewood Associates Inc.                                          |          1       0.07       0.07      86.49
        Deloitte & Touche LLP, Investment Arm                             |          1       0.07       0.07      86.56
        Delta Lloyd Private Equity                                        |          1       0.07       0.07      86.62
        Delta Partners                                                    |          1       0.07       0.07      86.69
        Desjardins Business Capital régional et coopératif                |          1       0.07       0.07      86.75
        Deutsche Venture Capital                                          |          1       0.07       0.07      86.82
        DnB NOR ASA, Investment Arm                                       |          1       0.07       0.07      86.89
        Downing LLP, Investment Arm                                       |          1       0.07       0.07      86.95
        Downing Ventures                                                  |          1       0.07       0.07      87.02
        E-venture Srl, Investment Arm                                     |          1       0.07       0.07      87.09
        EFG-Hermes Private Equity                                         |          1       0.07       0.07      87.15
        ELAN SBI Capital Partners                                         |          1       0.07       0.07      87.22
        EarlyBirdCapital Inc., Investment Arm                             |          1       0.07       0.07      87.28
        Eastgate Capital Group                                            |          1       0.07       0.07      87.35
        Efibanca S.p.A., Investment Arm                                   |          1       0.07       0.07      87.42
        Emigrant Capital Corp.                                            |          1       0.07       0.07      87.48
        Erste Group Bank AG, Investment Arm                               |          1       0.07       0.07      87.55
        European Investment Bank, Investment Arm                          |          1       0.07       0.07      87.62
        Evercore Capital Partners                                         |          1       0.07       0.07      87.68
        Evercore Ventures                                                 |          1       0.07       0.07      87.75
        Exponential Ventures                                              |          1       0.07       0.07      87.81
        F.N.B. Capital Corporation, LLC                                   |          1       0.07       0.07      87.88
        FINAM Investment Company, Investment Arm                          |          1       0.07       0.07      87.95
        Fanisi Capital Ltd.                                               |          1       0.07       0.07      88.01
        Financial Technology Partners LP, Investment Arm                  |          1       0.07       0.07      88.08
        First National Bank, Investment Arm                               |          1       0.07       0.07      88.15
        Five Arrows Managers SAS                                          |          1       0.07       0.07      88.21
        Fleet Development Ventures, LLC                                   |          1       0.07       0.07      88.28
        Focus Private Equity Partners                                     |          1       0.07       0.07      88.34
        Fortis Private Equity Venture Belgium S.A.                        |          1       0.07       0.07      88.41
        Fukui Bank, Investment Arm                                        |          1       0.07       0.07      88.48
        GCE Capital                                                       |          1       0.07       0.07      88.54
        GF Securities Co., Ltd., Investment Arm                           |          1       0.07       0.07      88.61
        GVA Capital                                                       |          1       0.07       0.07      88.68
        Gefinor Capital                                                   |          1       0.07       0.07      88.74
        Gold Stone Investment Co., Ltd.                                   |          1       0.07       0.07      88.81
        Goldman Sachs Specialty Lending Group L.P.                        |          1       0.07       0.07      88.87
        Goldman Sachs Strategic Investments Limited                       |          1       0.07       0.07      88.94
        Grenke Bank AG, Investment Arm                                    |          1       0.07       0.07      89.01
        Groupe BPCE, Investment Arm                                       |          1       0.07       0.07      89.07
        Guangdong Yuecai Venture Capital Investment Co., Ltd.             |          1       0.07       0.07      89.14
        Gulf Finance House (B.S.C) E.C., Investment Arm                   |          1       0.07       0.07      89.21
        Gunma Capital Co., Ltd.                                           |          1       0.07       0.07      89.27
        Guosen H&S Venture Capital Co., Ltd.                              |          1       0.07       0.07      89.34
        HSBC Capital (Canada) Inc.                                        |          1       0.07       0.07      89.40
        Hana Financial Investment Co., Ltd., Investment Arm               |          1       0.07       0.07      89.47
        Hanwha Investment&Securities Co., Ltd., Investment Arm            |          1       0.07       0.07      89.54
        Hauser Private Equity                                             |          1       0.07       0.07      89.60
        Heritas Capital Management Pte Ltd                                |          1       0.07       0.07      89.67
        Highgate EIS Tech Fund LLP                                        |          1       0.07       0.07      89.74
        Huatai Securities Co., Ltd., Investment Arm                       |          1       0.07       0.07      89.80
        IBB Beteiligungsgesellschaft mbH                                  |          1       0.07       0.07      89.87
        ICICI Investment Management Co., Ltd.                             |          1       0.07       0.07      89.93
        IFMR Ventures India Private Limited                               |          1       0.07       0.07      90.00
        ING Groep NV, Investment Arm                                      |          1       0.07       0.07      90.07
        Ibis Capital Partners, Inc., Investment Arm                       |          1       0.07       0.07      90.13
        Industrial Bank of Korea, Investment Arm                          |          1       0.07       0.07      90.20
        International Financial Corporation                               |          1       0.07       0.07      90.26
        Invernostra S.L.                                                  |          1       0.07       0.07      90.33
        Investec Growth & Acquisition Finance                             |          1       0.07       0.07      90.40
        Investec Ventures Ireland Ltd                                     |          1       0.07       0.07      90.46
        Investitions & Strukturbank Rheinland Pfalz GmbH, Investment Arm  |          1       0.07       0.07      90.53
        Ion Pacific Limited, Investment Arm                               |          1       0.07       0.07      90.60
        Istithmar World P.J.S.C.                                          |          1       0.07       0.07      90.66
        Ithmaar Bank, Private Equity                                      |          1       0.07       0.07      90.73
        J.P. Morgan (China) Venture Capital Investment Company Limited    |          1       0.07       0.07      90.79
        JBIC IG Partners                                                  |          1       0.07       0.07      90.86
        JM Financial Investment Managers Limited                          |          1       0.07       0.07      90.93
        KB Securities Co., Ltd., Investment Arm                           |          1       0.07       0.07      90.99
        KEB Hana Bank, Investment Arm                                     |          1       0.07       0.07      91.06
        KGI Asia Limited, Investment Arm                                  |          1       0.07       0.07      91.13
        KIT Finance Investment Bank, Investment Arm                       |          1       0.07       0.07      91.19
        Karoll Finance Ltd                                                |          1       0.07       0.07      91.26
        Keating Investments, LLC, Investment Arm                          |          1       0.07       0.07      91.32
        Korea Development Bank, Investment Arm                            |          1       0.07       0.07      91.39
        Korea Investment Partners Co. Ltd.                                |          1       0.07       0.07      91.46
        Krauter & Company, Investment Arm                                 |          1       0.07       0.07      91.52
        Krealo                                                            |          1       0.07       0.07      91.59
        Longhua Qifu Investment Co., Ltd.                                 |          1       0.07       0.07      91.66
        MU Hands-on Capital Ltd.                                          |          1       0.07       0.07      91.72
        Macquarie Funds Management (USA) Inc.                             |          1       0.07       0.07      91.79
        Manulife Capital                                                  |          1       0.07       0.07      91.85
        Meritz Securities Co., Ltd., Investment Arm                       |          1       0.07       0.07      91.92
        Methorios Capital S.p.A., Investment Arm                          |          1       0.07       0.07      91.99
        Mitsubishi UFJ Financial Group, Inc., Investment Arm              |          1       0.07       0.07      92.05
        Mitsubishi UFJ Trust And Banking Corporation, Investment Arm      |          1       0.07       0.07      92.12
        Mizuho Securities Principal Investment Co., Ltd.                  |          1       0.07       0.07      92.19
        Morgan Stanley Dean Witter Equity Funding, Inc.                   |          1       0.07       0.07      92.25
        NBT Capital Corp.                                                 |          1       0.07       0.07      92.32
        NIBC Infrastructure Partners                                      |          1       0.07       0.07      92.38
        NIBC Principal Investments B.V.                                   |          1       0.07       0.07      92.45
        NXT Capital Venture Finance                                       |          1       0.07       0.07      92.52
        National Australia Investment Capital Ltd.                        |          1       0.07       0.07      92.58
        New Access Investments                                            |          1       0.07       0.07      92.65
        New Business Investment Co., Ltd.                                 |          1       0.07       0.07      92.72
        New York Life Ventures                                            |          1       0.07       0.07      92.78
        ORIX Capital Corporation                                          |          1       0.07       0.07      92.85
        ORIX Corporation, Investment Arm                                  |          1       0.07       0.07      92.91
        ORIX Private Equity Korea Corporation                             |          1       0.07       0.07      92.98
        OSK Ventures International Berhad, Investment Arm                 |          1       0.07       0.07      93.05
        Oakwood Global Finance LLP                                        |          1       0.07       0.07      93.11
        Odysseus Investments Sarl                                         |          1       0.07       0.07      93.18
        Okasan Capital Partners Co., Ltd.                                 |          1       0.07       0.07      93.25
        Opus Bank, Investment Arm                                         |          1       0.07       0.07      93.31
        Osher Tech                                                        |          1       0.07       0.07      93.38
        OÜ Redgate Capital, Investment Arm                                |          1       0.07       0.07      93.44
        PC Capital                                                        |          1       0.07       0.07      93.51
        PT BCA Sekuritas, Investment Arm                                  |          1       0.07       0.07      93.58
        Palladian Capital Partners LLC                                    |          1       0.07       0.07      93.64
        Paluel-Marmont Capital SAS                                        |          1       0.07       0.07      93.71
        Par Equity LLP                                                    |          1       0.07       0.07      93.77
        Pekao Fundusz Kapitalowy Sp. z o.o                                |          1       0.07       0.07      93.84
        Pictet & Cie, Investment Arm                                      |          1       0.07       0.07      93.91
        Playford Capital Pty Ltd.                                         |          1       0.07       0.07      93.97
        Poalim Ventures Ltd.                                              |          1       0.07       0.07      94.04
        Portugal Capital Ventures - Sociedade de Capital de Risco, S.A.   |          1       0.07       0.07      94.11
        Poteza Nalozbe d.o.o.                                             |          1       0.07       0.07      94.17
        PowerOne Capital Markets Limited, Investment Arm                  |          1       0.07       0.07      94.24
        Presidio Investors LLC                                            |          1       0.07       0.07      94.30
        Puente Hnos. S.A., Investment Arm                                 |          1       0.07       0.07      94.37
        Puma Investment Management Limited                                |          1       0.07       0.07      94.44
        Pyrénées Gascogne Développement                                   |          1       0.07       0.07      94.50
        RMB Ventures Limited                                              |          1       0.07       0.07      94.57
        Renewal Capital LLC                                               |          1       0.07       0.07      94.64
        Richardson Capital Limited                                        |          1       0.07       0.07      94.70
        Riello Investimenti Partners SGR S.p.A                            |          1       0.07       0.07      94.77
        Riva y García Private Equity                                      |          1       0.07       0.07      94.83
        Riverside Management Group, Investment Arm                        |          1       0.07       0.07      94.90
        Roman Arch Funds                                                  |          1       0.07       0.07      94.97
        Rothschild Ventures Asia Pte. Ltd.                                |          1       0.07       0.07      95.03
        Royal Bank Ventures Ltd.                                          |          1       0.07       0.07      95.10
        S MittelstandsKapital KölnBonn GmbH                               |          1       0.07       0.07      95.17
        SBI Securities Co, Investment Arm                                 |          1       0.07       0.07      95.23
        SEPI Desarrollo Empresarial, S.A., S.M.E.                         |          1       0.07       0.07      95.30
        SFS Group Public Company Ltd., Investment Arm                     |          1       0.07       0.07      95.36
        SNS Reaal Invest                                                  |          1       0.07       0.07      95.43
        Sabadell Capital                                                  |          1       0.07       0.07      95.50
        Santander Bank, N. A., Investment Arm                             |          1       0.07       0.07      95.56
        Sberbank-Capital JSC                                              |          1       0.07       0.07      95.63
        Schroder & Co. Bank AG, Investment Arm                            |          1       0.07       0.07      95.70
        Secus Asset Management S.A., Private Equity Arm                   |          1       0.07       0.07      95.76
        SenaHill Investment Group, LLC                                    |          1       0.07       0.07      95.83
        Senshu Ikeda Capital Co., Ltd.                                    |          1       0.07       0.07      95.89
        Shanghai Yunxin Venture Capital Co., Ltd.                         |          1       0.07       0.07      95.96
        Shigagin Lease Capital Co.,Ltd.                                   |          1       0.07       0.07      96.03
        Shinhan Bank, Investment Arm                                      |          1       0.07       0.07      96.09
        Shinhan Investment Corp., Investment Arm                          |          1       0.07       0.07      96.16
        Shinsei Corporate Investment Limited                              |          1       0.07       0.07      96.23
        ShoreCap Management                                               |          1       0.07       0.07      96.29
        Sociedad de Promoción y Participación Empresarial Caja de Madrid, |          1       0.07       0.07      96.36
        S.A.                                                              |                                            
        Société Générale Capital Partenaires SAS, SCR                     |          1       0.07       0.07      96.42
        Société Générale Ventures                                         |          1       0.07       0.07      96.49
        Sofilaro S.A.S.                                                   |          1       0.07       0.07      96.56
        Sony Financial Ventures Inc.                                      |          1       0.07       0.07      96.62
        Soochow Venture Capital Co., Ltd.                                 |          1       0.07       0.07      96.69
        Soundview Technology, Investment Arm                              |          1       0.07       0.07      96.75
        Spara Merchant Capital Corp.                                      |          1       0.07       0.07      96.82
        Stanford Venture Capital Holdings, Inc.                           |          1       0.07       0.07      96.89
        Starr Investment Holdings, LLC                                    |          1       0.07       0.07      96.95
        Subhkam Ventures                                                  |          1       0.07       0.07      97.02
        Sun Hung Kai Strategic Capital Limited, Investment Arm            |          1       0.07       0.07      97.09
        SunAmerica Ventures                                               |          1       0.07       0.07      97.15
        Susquehanna Private Equity Investments, LLC                       |          1       0.07       0.07      97.22
        Swiss Re Alternative Investments                                  |          1       0.07       0.07      97.28
        Symbion Capital I A/S                                             |          1       0.07       0.07      97.35
        Syncora Alternative Investments LLC                               |          1       0.07       0.07      97.42
        TD Capital                                                        |          1       0.07       0.07      97.48
        TPH Partners, LLC                                                 |          1       0.07       0.07      97.55
        TVC Capital, LLC                                                  |          1       0.07       0.07      97.62
        Tata Capital Pte. Limited                                         |          1       0.07       0.07      97.68
        The Pacific Securities Co., Ltd., Investment Arm                  |          1       0.07       0.07      97.75
        Thomas Weisel Capital Management, LLC                             |          1       0.07       0.07      97.81
        Tianfeng Securities Brokerage Co., Ltd., Investment Arm           |          1       0.07       0.07      97.88
        Tottori Capital Co., Ltd.                                         |          1       0.07       0.07      97.95
        Toyo Capital Co., Ltd.                                            |          1       0.07       0.07      98.01
        TrustCapital NV                                                   |          1       0.07       0.07      98.08
        U.S. Trust Private Equity                                         |          1       0.07       0.07      98.15
        UMB Capital Corporation                                           |          1       0.07       0.07      98.21
        Ubequity Capital Partners Inc., Investment Arm                    |          1       0.07       0.07      98.28
        Union d'Etudes et d'Investissements                               |          1       0.07       0.07      98.34
        Unitus Ventures                                                   |          1       0.07       0.07      98.41
        VR Equitypartner GmbH                                             |          1       0.07       0.07      98.48
        Value Italy SGR S.p.A.                                            |          1       0.07       0.07      98.54
        Ventegis Capital AG                                               |          1       0.07       0.07      98.61
        Virtu Financial Inc, Investment Arm                               |          1       0.07       0.07      98.68
        Virðing hf., Private Equity                                       |          1       0.07       0.07      98.74
        Vunani Limited, Investment Arm                                    |          1       0.07       0.07      98.81
        WM Strategic Capital                                              |          1       0.07       0.07      98.87
        WS Capital, LLC                                                   |          1       0.07       0.07      98.94
        WWB Asset Management                                              |          1       0.07       0.07      99.01
        Wachovia Private Capital, Inc.                                    |          1       0.07       0.07      99.07
        Warson Capital Partners, LLC, Investment Arm                      |          1       0.07       0.07      99.14
        Wells Fargo Energy Capital Inc.                                   |          1       0.07       0.07      99.21
        WestLB AG - Private Equity Investments                            |          1       0.07       0.07      99.27
        Women's World Banking Capital Partners, LP                        |          1       0.07       0.07      99.34
        Woori Private Equity Asset Management                             |          1       0.07       0.07      99.40
        X-Ventures                                                        |          1       0.07       0.07      99.47
        Yamanashi Chugin Management Consulting Co., Ltd., Investment Arm  |          1       0.07       0.07      99.54
        Yorkton Securities Inc., Investment Arm                           |          1       0.07       0.07      99.60
        Zeus Capital Limited, Investment Arm                              |          1       0.07       0.07      99.67
        eBest Investment Securities Co., Ltd., Investment Arm             |          1       0.07       0.07      99.74
        i capital, Investment Arm                                         |          1       0.07       0.07      99.80
        iD Ventures America, LLC                                          |          1       0.07       0.07      99.87
        inovaBra Ventures                                                 |          1       0.07       0.07      99.93
        Íslandsbanki, Investment Arm                                      |          1       0.07       0.07     100.00
        Total                                                             |       1510     100.00     100.00           
-----------------------------------------------------------------------------------------------------------------------

. 
. keep if (Company_Type_=="Corporate Investment Arm" | Company_Type_=="Financial Service Investment Arm")
(20,353 observations deleted)

. tab period

     period |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        397       15.29       15.29
          2 |        365       14.06       29.35
          3 |        559       21.53       50.89
          4 |      1,275       49.11      100.00
------------+-----------------------------------
      Total |      2,596      100.00

. 
. * Corporate
. 
. merge m:1 BuyersInvestors using corpvcmapping

    Result                      Number of obs
    -----------------------------------------
    Not matched                         1,510
        from master                     1,510  (_merge==1)
        from using                          0  (_merge==2)

    Matched                             1,086  (_merge==3)
    -----------------------------------------

. drop _merge

. gen CVCtype="Bank" if Bank==1
(2,521 missing values generated)

. replace CVCtype="OtherFin" if OtherFin==1
variable CVCtype was str4 now str8
(75 real changes made)

. replace CVCtype="Payments" if Payment==1
(23 real changes made)

. replace CVCtype="IT Other" if (Other==1 | IT==1)
(441 real changes made)

. tab BuyersInv if Drop==1, sort

                        BuyersInvestors |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
     Enterprise Ireland, Investment Arm |         22        4.66        4.66
            Octopus Investments Limited |         13        2.75        7.42
                 Fenway Summer Ventures |         12        2.54        9.96
                            PROPARCO SA |         12        2.54       12.50
Internet Initiatives Development Fund.. |         11        2.33       14.83
                       NXTP Labs S.R.L. |         11        2.33       17.16
Ben Franklin Technology Partners of S.. |          9        1.91       19.07
  Endeavor Global, Inc., Investment Arm |          9        1.91       20.97
                          Kapor Capital |          8        1.69       22.67
                Globis Capital Partners |          7        1.48       24.15
     Capital Enterprise, Investment Arm |          6        1.27       25.42
            Metropolitan Partners Group |          6        1.27       26.69
             Novel TMT Ventures Limited |          6        1.27       27.97
                      Orange Capital SA |          6        1.27       29.24
                         Vulcan Capital |          6        1.27       30.51
                         Beedie Capital |          5        1.06       31.57
   Dieter von Holtzbrinck Ventures GmbH |          5        1.06       32.63
          Fortress Investment Group LLC |          5        1.06       33.69
            Pamodzi Investment Holdings |          5        1.06       34.75
       Project A Ventures GmbH & Co. KG |          5        1.06       35.81
                       SoftBank Capital |          5        1.06       36.86
    Tengelmann Ventures Management GmbH |          5        1.06       37.92
The National Digital Research Centre .. |          5        1.06       38.98
                                  ALLVP |          4        0.85       39.83
                        Astarc Ventures |          4        0.85       40.68
  Flare Capital Management Company, LLC |          4        0.85       41.53
             Montagu Private Equity LLP |          4        0.85       42.37
New York City Investment Fund Manager.. |          4        0.85       43.22
                             SGInnovate |          4        0.85       44.07
              TVS Capital Funds Limited |          4        0.85       44.92
               VCET Capital Corporation |          4        0.85       45.76
                          CIT GAP Funds |          3        0.64       46.40
              Captii Ventures Pte. Ltd. |          3        0.64       47.03
Dublin Business Innovation Centre, In.. |          3        0.64       47.67
              EDB Investments Pte. Ltd. |          3        0.64       48.31
                  Formula Ventures Ltd. |          3        0.64       48.94
    Gray Matters Capital, Endowment Arm |          3        0.64       49.58
                           Manvest Inc. |          3        0.64       50.21
        Nesta Investment Management LLP |          3        0.64       50.85
     Performance Equity Management, LLC |          3        0.64       51.48
                          Principia SGR |          3        0.64       52.12
                                  TLabs |          3        0.64       52.75
                    The North West Fund |          3        0.64       53.39
       WDB Investment Holdings Pty Ltd. |          3        0.64       54.03
Aerospace Science & Industry Asset Ma.. |          2        0.42       54.45
 Aga Khan Fund for Economic Development |          2        0.42       54.87
            Anschutz Investment Company |          2        0.42       55.30
     Dubai International Capital L.L.C. |          2        0.42       55.72
                    Foresight Group LLP |          2        0.42       56.14
                            GemVentures |          2        0.42       56.57
Gestión de Capital Riesgo del País Va.. |          2        0.42       56.99
Great White Shark Enterprises, Inc, I.. |          2        0.42       57.42
                   JD Capital Co., Ltd. |          2        0.42       57.84
Lunds Universitets Innovationssystem AB |          2        0.42       58.26
                        MAIF Avenir SAS |          2        0.42       58.69
      McCarthy Partners Management, LLC |          2        0.42       59.11
                            NOM Finance |          2        0.42       59.53
                 North-East Venture A/S |          2        0.42       59.96
  Ona Capital Privat, SCR de R.S., S.A. |          2        0.42       60.38
                  Opt Ventures Co, Ltd. |          2        0.42       60.81
Shanghai Yonghua Capital Management C.. |          2        0.42       61.23
       Singapore Angel Network Pte. Ltd |          2        0.42       61.65
                Sistema Venture Capital |          2        0.42       62.08
        Softbank China & India Holdings |          2        0.42       62.50
                Spiral Ventures Pte Ltd |          2        0.42       62.92
                Sprout Venture Partners |          2        0.42       63.35
   Vorwerk Direct Selling Ventures GmbH |          2        0.42       63.77
                    Work-Bench Ventures |          2        0.42       64.19
Zhuhai Huachuang Investment Managemen.. |          2        0.42       64.62
                              @Ventures |          1        0.21       64.83
     A2F Consulting LLC, Investment Arm |          1        0.21       65.04
                            AE Ventures |          1        0.21       65.25
                AL Arif Investments LLC |          1        0.21       65.47
            Accelerasia, Investment Arm |          1        0.21       65.68
                         Admitad Invest |          1        0.21       65.89
        Ann Arbor SPARK, Investment Arm |          1        0.21       66.10
  Aquila Infrastructure Management Inc. |          1        0.21       66.31
        Arizona Bay Technology Ventures |          1        0.21       66.53
   Arnela Capital Privado, S.C.R., S.A. |          1        0.21       66.74
                                 Arrive |          1        0.21       66.95
       Artificial Life Investments Ltd. |          1        0.21       67.16
                  Arzan Venture Capital |          1        0.21       67.37
                     Ascension Ventures |          1        0.21       67.58
                  Avista Ventures, Inc. |          1        0.21       67.80
    Axiata Group Berhad, Investment Arm |          1        0.21       68.01
     B2B Infrastructure Investment Fund |          1        0.21       68.22
                       BAMS Angels Fund |          1        0.21       68.43
BRAINWORKS Capital Management (Privat.. |          1        0.21       68.64
                           BXA Ventures |          1        0.21       68.86
Banif Capital - Sociedade de Capital .. |          1        0.21       69.07
                        Beenos Partners |          1        0.21       69.28
                        BitFury Capital |          1        0.21       69.49
Blackbirch Capital Inc., Investment Arm |          1        0.21       69.70
         Bokwang Investment Corporation |          1        0.21       69.92
          Bonsai Venture Capital SA SCR |          1        0.21       70.13
           Bouygues Telecom Initiatives |          1        0.21       70.34
Business Leaders For Michigan, Invest.. |          1        0.21       70.55
                           CAA Ventures |          1        0.21       70.76
                  Cambridge Innovations |          1        0.21       70.97
           CincyTechUSA, Investment Arm |          1        0.21       71.19
Clal Industries and Investments Ltd.,.. |          1        0.21       71.40
                            CommIT, LLC |          1        0.21       71.61
                    Cyberworks Ventures |          1        0.21       71.82
                  DOEN Participaties BV |          1        0.21       72.03
                     Danone Communities |          1        0.21       72.25
             DeNA Venture Capital Group |          1        0.21       72.46
Dowling & Partners Securities, LLC, I.. |          1        0.21       72.67
                        Downey Ventures |          1        0.21       72.88
                      Dunamu & Partners |          1        0.21       73.09
               Edenred Capital Partners |          1        0.21       73.31
Empresa Nacional de Innovación, SME, .. |          1        0.21       73.52
Engineers Without Borders Canada, End.. |          1        0.21       73.73
                        Evergy Ventures |          1        0.21       73.94
            Evonik Venture Capital GmbH |          1        0.21       74.15
              FSE Fund Managers Limited |          1        0.21       74.36
               Fifth Street Capital LLC |          1        0.21       74.58
           Freebit Investment Co., Ltd. |          1        0.21       74.79
                Fuchsia Venture Capital |          1        0.21       75.00
             Fuji Startup Ventures Inc. |          1        0.21       75.21
 Fundepar Gestão De Investimentos Ltda. |          1        0.21       75.42
                           GC1 Ventures |          1        0.21       75.64
                        GO Ventures LLC |          1        0.21       75.85
                     Generator Ventures |          1        0.21       76.06
                   German Ventures GmbH |          1        0.21       76.27
                Gibraltar Ventures, LLC |          1        0.21       76.48
                 Gordon Brothers Europe |          1        0.21       76.69
                            HCM Capital |          1        0.21       76.91
Hamilton Venture Capital Ltd, Investm.. |          1        0.21       77.12
                     HardGamma Ventures |          1        0.21       77.33
                            Hi Inov SAS |          1        0.21       77.54
High Impact Capital Advisors Ltd., In.. |          1        0.21       77.75
                      Hollinger Capital |          1        0.21       77.97
Hong Kong Cyberport Management Compan.. |          1        0.21       78.18
       Hyield Venture Capital Co., Ltd. |          1        0.21       78.39
              IBERDROLA Ventures-PERSEO |          1        0.21       78.60
                    IDC Venture Capital |          1        0.21       78.81
                      INTRO Invest GmbH |          1        0.21       79.03
                 InVent Venture Capital |          1        0.21       79.24
                          InVivo Invest |          1        0.21       79.45
                           Incutex S.A. |          1        0.21       79.66
                 Infineon Ventures GmbH |          1        0.21       79.87
                  Ingenico Ventures SAS |          1        0.21       80.08
                          Initiative IP |          1        0.21       80.30
          Isetan Mitsukoshi Innovations |          1        0.21       80.51
                   Itochu Finance Corp. |          1        0.21       80.72
 Jiangsu Tech industry Investment Corp. |          1        0.21       80.93
 Jiangyin Huaxicun Investment Co., Ltd. |          1        0.21       81.14
              KPC Energy Ventures, Inc. |          1        0.21       81.36
               Kalonia Venture Partners |          1        0.21       81.57
                 Kirnaf Finance Company |          1        0.21       81.78
      Knight Foundation, Investment Arm |          1        0.21       81.99
            Le B612 Participations, SAS |          1        0.21       82.20
Lhasa Bainian Dehua Investment Co., L.. |          1        0.21       82.42
        Liberate Corporate Venture Fund |          1        0.21       82.63
       Liberty Israel Venture Fund, LLC |          1        0.21       82.84
                         MGEN Tech Fund |          1        0.21       83.05
MaRs Discovery District, Investment Arm |          1        0.21       83.26
               Mad'a Investment Company |          1        0.21       83.47
        Maotian Capital Company Limited |          1        0.21       83.69
                 Masdar Venture Capital |          1        0.21       83.90
                      MediaTek Ventures |          1        0.21       84.11
Meltwater Entrepreneurial School of T.. |          1        0.21       84.32
Metropole Nice Cote D'azur, Endowment.. |          1        0.21       84.53
                         Nem SGR S.p.A. |          1        0.21       84.75
                            Next47 GmbH |          1        0.21       84.96
  Noah Holdings Limited, Investment Arm |          1        0.21       85.17
               Nogle Capital Management |          1        0.21       85.38
North Industries Group Investment Man.. |          1        0.21       85.59
                      OCI Venture Group |          1        0.21       85.81
                          Oltre Venture |          1        0.21       86.02
                      Omnivore Partners |          1        0.21       86.23
One97 Communications Limited, Investm.. |          1        0.21       86.44
                             Orange Fab |          1        0.21       86.65
              Orchestra Investment Inc. |          1        0.21       86.86
PICC Capital Investment Management Co.. |          1        0.21       87.08
                              PSG Alpha |          1        0.21       87.29
     Panda Capital Management Co., Ltd. |          1        0.21       87.50
                         Raise Ventures |          1        0.21       87.71
                       Reaktor Ventures |          1        0.21       87.92
        Residex Venture Capital Network |          1        0.21       88.14
          Rev1 Ventures, Investment Arm |          1        0.21       88.35
              SEED Venture Finance, LLC |          1        0.21       88.56
  SGAM AG2R La Mondiale, Investment Arm |          1        0.21       88.77
                   SIX FinTech Ventures |          1        0.21       88.98
                           SKT Ventures |          1        0.21       89.19
               Saison Capital Pte. Ltd. |          1        0.21       89.41
              Saison Ventures Co., Ltd. |          1        0.21       89.62
    Shanghai Daofeng Investment Co. Ltd |          1        0.21       89.83
Shanghai International Group Assets M.. |          1        0.21       90.04
       Shizuoka Capital Company Limited |          1        0.21       90.25
             Showcase Capital Co., Ltd. |          1        0.21       90.47
                           Sofiouest SA |          1        0.21       90.68
                 SoftBank Ventures Asia |          1        0.21       90.89
              Softline Venture Partners |          1        0.21       91.10
Southeast University Education Founda.. |          1        0.21       91.31
                  Sphere Private Equity |          1        0.21       91.53
Strada Education Network, Endownment .. |          1        0.21       91.74
           Suez Asia Holdings Pte. Ltd. |          1        0.21       91.95
                    Supply Chain Angels |          1        0.21       92.16
     Suzhou Haihui Investment Co., Ltd. |          1        0.21       92.37
                      Syngenta Ventures |          1        0.21       92.58
            TBS Innovation Partners LLC |          1        0.21       92.80
                            TI Ventures |          1        0.21       93.01
                           TIM Ventures |          1        0.21       93.22
Taipei Fubon Commercial Bank Co., Ltd.. |          1        0.21       93.43
   The Benaroya Company, Investment Arm |          1        0.21       93.64
                   The Innovation Group |          1        0.21       93.86
             The Next 36, Endowment Arm |          1        0.21       94.07
The University of Tokyo Edge Capital .. |          1        0.21       94.28
         The Whittemore Collection Ltd. |          1        0.21       94.49
Three Gorges Capital Holdings Co., Ltd. |          1        0.21       94.70
Tibet Gongbo gyamda Jiusheng Investme.. |          1        0.21       94.92
Tongfang Financial Holding (Shenzhen).. |          1        0.21       95.13
Tongfang Financial Holdings (Shenzhen.. |          1        0.21       95.34
       Total Carbon Neutrality Ventures |          1        0.21       95.55
Transcosmos Investments & Business De.. |          1        0.21       95.76
                    UNIQA Ventures GmbH |          1        0.21       95.97
   UTokyo Innovation Platform Co., Ltd. |          1        0.21       96.19
              Vectren Enterprises, Inc. |          1        0.21       96.40
               VentureTech Alliance LLC |          1        0.21       96.61
                Verein Innovationsfonds |          1        0.21       96.82
         Volvo Group Venture Capital AB |          1        0.21       97.03
       Wooshin Venture Investment Corp. |          1        0.21       97.25
Wuhan Economic Development and Invest.. |          1        0.21       97.46
                           XTX Ventures |          1        0.21       97.67
       Xiamen CCRE Investment Co., Ltd. |          1        0.21       97.88
                                 Xpring |          1        0.21       98.09
YeahMobi Information Technology Co., .. |          1        0.21       98.31
                Yicun Capital Co., Ltd. |          1        0.21       98.52
Zhejiang Baoxiniao Venture Capital Co.. |          1        0.21       98.73
                   divine InterVentures |          1        0.21       98.94
                             e-partners |          1        0.21       99.15
                      i Mercury Capital |          1        0.21       99.36
             iSigma Capital Corporation |          1        0.21       99.58
                           iXL Ventures |          1        0.21       99.79
                    nChain Reaction Ltd |          1        0.21      100.00
----------------------------------------+-----------------------------------
                                  Total |        472      100.00

. drop if Drop==1
(472 observations deleted)

. drop if (Bank==. & OtherFin==. & Payment==. & Other==. & IT==. & Drop==.) & Company_Type_=="Corporate Investment Arm"
(0 observations deleted)

. drop Bank OtherFin Payment Other IT Drop

. 
. * Fin
. 
. merge m:1 BuyersInvestors using finvcmapping

    Result                      Number of obs
    -----------------------------------------
    Not matched                           899
        from master                       899  (_merge==1)
        from using                          0  (_merge==2)

    Matched                             1,225  (_merge==3)
    -----------------------------------------

. drop _merge

. replace CVCtype="Bank" if Bank==1
(183 real changes made)

. replace CVCtype="OtherFin" if OtherFin==1
(67 real changes made)

. replace CVCtype="Payments" if Payment==1
(0 real changes made)

. replace CVCtype="IT Other" if (Other==1 | IT==1)
(28 real changes made)

. drop if Drop==1
(830 observations deleted)

. drop if (Bank==. & OtherFin==. & Payment==. & Other==. & IT==. & Drop==.) & Company_Type_=="Financial Service Investme
> nt Arm"
(402 observations deleted)

. drop Bank OtherFin Payment Other IT Drop

. 
. * Trimming non-VC
. 
. drop if (TotalTr>500 & TotalTr~=.)
(15 observations deleted)

. 
. * Fixing for analysis
. 
. gen normamount=TotalTransactionValueUSDmm/maxcount
(164 missing values generated)

. drop if Company_Country_~="United States"
(482 observations deleted)

. by year, sort: egen yeartot=sum(normamount)

. tab year, sum(yeartot)

            |         Summary of yeartot
       year |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   277.15298           0          51
       2001 |   36.470833           0          11
       2002 |       15.75           0           4
       2003 |       39.07           0           6
       2004 |    4.405076           0           3
       2005 |    9.666667           0           4
       2006 |   9.9925003           0           6
       2007 |     11.1875           0           5
       2008 |           0           0           1
       2009 |   31.501667           0           6
       2010 |   75.990005           0          10
       2011 |   236.35667           0          12
       2012 |   90.577499           0          12
       2013 |   70.433502           0          18
       2014 |   57.403358           0          16
       2015 |   215.31393           0          35
       2016 |   198.87242           0          39
       2017 |   233.44353           0          47
       2018 |     359.784           0          45
       2019 |   472.87253           0          64
------------+------------------------------------
      Total |   239.94312   142.84615         395

. drop yeartot

. by period CVCtype, sort: egen total=sum(normamount) 

. drop if period==.
(0 observations deleted)

. by period CVCtype, sort: drop if _n~=1 
(382 observations deleted)

. 
. list period CVCtype total 

     +------------------------------+
     | period    CVCtype      total |
     |------------------------------|
  1. |      1       Bank   117.1341 |
  2. |      1   IT Other   219.4565 |
  3. |      1   OtherFin   36.25833 |
  4. |      2       Bank   24.41667 |
  5. |      2   IT Other   37.93167 |
     |------------------------------|
  6. |      3       Bank   150.5417 |
  7. |      3   IT Other   356.1034 |
  8. |      3   OtherFin     20.512 |
  9. |      3   Payments      3.604 |
 10. |      4       Bank   245.3055 |
     |------------------------------|
 11. |      4   IT Other   729.6854 |
 12. |      4   OtherFin   427.9949 |
 13. |      4   Payments   77.30059 |
     +------------------------------+

. 
. 
. 
. ***FINPATTREND.TXT
. 
. clear 

. 
. use financial_patent_data_v3

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   patent_id |     24,255     8447202    921178.4    6173891   1.02e+07
    app_date |     24,255    17955.64    1681.123      14612      21447
    app_year |     24,255    2008.652    4.611431       2000       2018
  grant_date |     24,255    19326.14    1352.905      14991      21606
 primary_cpc |          0
-------------+---------------------------------------------------------
cpc_subclass |          0
  cite_count |     24,255    12.07607    31.09662          0        601
  mean_cites |     24,255    10.69635    13.40186          0   163.1282
weighted_c~e |     24,252    1.249208    3.446227          0   102.0472
assignee_t~e |     22,365    2.199955    .4481624          2          7
-------------+---------------------------------------------------------
kogan_etal~l |      9,499    53.60786    107.2379   .0006292   1940.746
kelly_eta~10 |     18,155    1.335914    1.040012          0   8.988219
kelly_etal~5 |     18,155    .8571892     .472032          0   3.978838
       state |          0
  state_fips |     19,153    24.71232    16.22884          1         78
-------------+---------------------------------------------------------
    csa_code |     15,577    356.7765    136.5198        104        566
   csa_title |          0
inventor_1~y |          0
assignee_1~y |          0
vc_num_deals |     15,441    459.9734    562.5651          0       2306
-------------+---------------------------------------------------------
vc_sum_equ~d |     15,441    4872.898    7419.168          0   55689.49
us_ai_rank~g |      8,085    2.396908      1.6098          1          6
  accounting |     24,255    .0420914    .1596893          0          1
investment~g |     24,255    .0785083    .2274502          0          1
commercial~g |     24,255    .0504765    .1684729          0          1
-------------+---------------------------------------------------------
communicat~s |     24,255    .1389632    .2737019          0          1
    payments |     24,255    .3731844    .3771753          0          1
cryptocurr~y |     24,255    .0115153    .0670557          0          1
    currency |     24,255    .0057265    .0593467          0          1
   insurance |     24,255    .0132671    .0992131          0          1
-------------+---------------------------------------------------------
 real_estate |     24,255    .0133779     .090717          0          1
retail_ban~g |     24,255    .0606465    .1807701          0          1
    security |     24,255    .1979814    .3110459          0          1
wealth_man~t |     24,255    .0142615    .1015904          0          1
pae_initia~t |     24,255    .0176458    .1316631          0          1
-------------+---------------------------------------------------------
assignee_1~e |          0
pae_reassi~t |     24,255    .0109256    .1039551          0          1
reassignme~e |          0
pae_reassi~e |        265    18763.75    1303.724      14650      21137
    capiq_id |          0
-------------+---------------------------------------------------------
company_name |          0
     revenue |     13,346    29808.75    42680.09          0     485651
      ebitda |     10,353    5460.739    8671.517     -13595      82487
  rd_expense |      5,629    2099.578    2818.713     .05687      28837
advertisin~e |      6,281    765.7837    1072.822       .001   11541.87
-------------+---------------------------------------------------------
  net_income |     13,438    3141.358    6247.718     -99289      53394
        cash |     13,192     16046.1    48444.66    -.04757     331285
long_term_~t |     10,625    49249.73    144512.4    -5.9612    2944357
short_term~t |      8,184    57247.24    118859.5          0    1099811
short_term~s |      9,401    34604.06    105264.5          0     824318
-------------+---------------------------------------------------------
shareholde~y |     13,234    30338.87    53621.34     -50391     267146
  market_cap |     11,411    69433.16    86006.04     .00821   860882.5
  employment |     12,173    93562.38    174450.2          7    2300000
year_founded |     17,659    1945.101    59.14909       1727       2018
 age_of_firm |     17,659    73.89943    59.14909          1        292
-------------+---------------------------------------------------------
 global_sifi |     24,255    .0627912     .242592          0          1
primary_in~y |          0
primary_in~e |          0
gics_secto~e |          0
gics_group~e |          0
-------------+---------------------------------------------------------
gics_indus~e |          0
 gics_sector |          0
gics_indus~s |          0
revenue_gr~p |          0
      public |     24,255    .4704597    .4991369          0          1
-------------+---------------------------------------------------------
   vc_backed |     24,255    .0496392     .217203          0          1
          bs |     23,197    813884.3    450114.8        580    2377940
          fs |     23,197    782923.3    436854.3          0    2374299
    division |          0

. 
. * Clean up
. 
. gen aw_year=year(grant_date)

. 
. * 7 industries
. 
. gen bank=(primary_industry=="Diversified Banks" | primary_industry=="Regional Banks" | primary_industry=="Thrifts and 
> Mortgage Finance")

. gen capmkt=(primary_industry=="Asset Management and Custody Banks" | primary_industry=="Diversified Capital Markets" |
>  primary_industry=="Diversified REITs" | primary_industry=="Financial Exchanges and Data" | primary_industry=="Investm
> ent Banking and Brokerage" | primary_industry=="Specialized REITs") 

. gen consfin=(primary_industry=="Consumer Finance" | primary_industry=="Specialized Finance")

. gen insur=(primary_industry=="Life and Health Insurance" | primary_industry=="Multi-line Insurance" | primary_industry
> =="Property and Casualty Insurance" | primary_industry=="Reinsurance")

. gen pay=(primary_industry=="Data Processing and Outsourced Services")

. gen it=(primary_industry=="Application Software" | primary_industry=="Communications Equipment" | primary_industry=="C
> onsumer Electronics" | primary_industry=="Electrical Components and Equipment" | primary_industry=="Electronic Compone
> nts")

. replace it=1 if (primary_industry=="IT Consulting and Other Services" | primary_industry=="Electronic Equipment and In
> struments" | primary_industry=="Electronic Manufacturing Services" | primary_industry=="Integrated Telecommunication S
> ervices" | primary_industry=="Interactive Media and Services")
(1,967 real changes made)

. replace it=1 if (primary_industry=="Internet Services and Infrastructure" | primary_industry=="Internet and Direct Mar
> keting Retail" | primary_industry=="Semiconductor Equipment" | primary_industry=="Semiconductors" | primary_industry==
> "Specialized Consumer Services" | primary_industry=="Systems Software")
(1,862 real changes made)

. replace it=1 if (primary_industry=="Technology Distributors" | primary_industry=="Technology Hardware, Storage and Per
> ipherals" | primary_industry=="Wireless Telecommunication Services")
(1,883 real changes made)

. gen otherind=(bank==0 & capmkt==0 & consfin==0 & insur==0 & it==0)

. gen industrytype=1 if bank==1
(22,654 missing values generated)

. replace industrytype=2 if capmkt==1
(1,618 real changes made)

. replace industrytype=3 if consfin==1
(715 real changes made)

. replace industrytype=4 if insur==1
(1,098 real changes made)

. replace industrytype=5 if pay==1
(2,390 real changes made)

. replace industrytype=6 if it==1
(9,057 real changes made)

. replace industrytype=7 if industrytype==.
(7,776 real changes made)

. label define industrytype1 1 "bank" 2 "capmkt" 3 "consfin" 4 "insur" 5 "payments" 6 "it" 7 "otherind" 

. label values industrytype industrytype1

. gen indsimpletype=1 if bank==1
(22,654 missing values generated)

. replace indsimpletype=2 if (capmkt==1 | consfin==1 | insur==1)
(3,431 real changes made)

. replace indsimpletype=5 if pay==1
(2,390 real changes made)

. replace indsimpletype=6 if (it==1 | industrytype==7)
(16,833 real changes made)

. label define indsimpletype1 1 "Bank" 2 "Other Finance" 5 "Payments" 6 "IT and Other" 

. label values indsimpletype indsimpletype1

. 
. * 3 applications
. 
. gen payapp=(payments>=0.5)

. gen bankapp=(commercial_banking+investment_banking+retail_banking>=0.5)

. gen otherapp=(bankapp~=1 & payapp~=1)

. gen apptype=1 if payapp==1
(13,601 missing values generated)

. replace apptype=2 if bankapp==1
(5,486 real changes made)

. replace apptype=3 if apptype==.
(9,924 real changes made)

. label define apptype1 1 "payments" 2 "banking" 3 "otherapp"

. label values apptype apptype1

. 
. * 2 geographies
. 
. gen us=(inventor_1_country=="US")

. gen othernation=(us==0)

. gen nationtype=1 if us==1
(5,103 missing values generated)

. replace nationtype=2 if nationtype==.
(5,103 real changes made)

. label define nationtype1 1 "us" 2 "not us"

. label values nationtype nationtype1 

. save financial_patent_data_temp, replace
file financial_patent_data_temp.dta saved

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   patent_id |     24,255     8447202    921178.4    6173891   1.02e+07
    app_date |     24,255    17955.64    1681.123      14612      21447
    app_year |     24,255    2008.652    4.611431       2000       2018
  grant_date |     24,255    19326.14    1352.905      14991      21606
 primary_cpc |          0
-------------+---------------------------------------------------------
cpc_subclass |          0
  cite_count |     24,255    12.07607    31.09662          0        601
  mean_cites |     24,255    10.69635    13.40186          0   163.1282
weighted_c~e |     24,252    1.249208    3.446227          0   102.0472
assignee_t~e |     22,365    2.199955    .4481624          2          7
-------------+---------------------------------------------------------
kogan_etal~l |      9,499    53.60786    107.2379   .0006292   1940.746
kelly_eta~10 |     18,155    1.335914    1.040012          0   8.988219
kelly_etal~5 |     18,155    .8571892     .472032          0   3.978838
       state |          0
  state_fips |     19,153    24.71232    16.22884          1         78
-------------+---------------------------------------------------------
    csa_code |     15,577    356.7765    136.5198        104        566
   csa_title |          0
inventor_1~y |          0
assignee_1~y |          0
vc_num_deals |     15,441    459.9734    562.5651          0       2306
-------------+---------------------------------------------------------
vc_sum_equ~d |     15,441    4872.898    7419.168          0   55689.49
us_ai_rank~g |      8,085    2.396908      1.6098          1          6
  accounting |     24,255    .0420914    .1596893          0          1
investment~g |     24,255    .0785083    .2274502          0          1
commercial~g |     24,255    .0504765    .1684729          0          1
-------------+---------------------------------------------------------
communicat~s |     24,255    .1389632    .2737019          0          1
    payments |     24,255    .3731844    .3771753          0          1
cryptocurr~y |     24,255    .0115153    .0670557          0          1
    currency |     24,255    .0057265    .0593467          0          1
   insurance |     24,255    .0132671    .0992131          0          1
-------------+---------------------------------------------------------
 real_estate |     24,255    .0133779     .090717          0          1
retail_ban~g |     24,255    .0606465    .1807701          0          1
    security |     24,255    .1979814    .3110459          0          1
wealth_man~t |     24,255    .0142615    .1015904          0          1
pae_initia~t |     24,255    .0176458    .1316631          0          1
-------------+---------------------------------------------------------
assignee_1~e |          0
pae_reassi~t |     24,255    .0109256    .1039551          0          1
reassignme~e |          0
pae_reassi~e |        265    18763.75    1303.724      14650      21137
    capiq_id |          0
-------------+---------------------------------------------------------
company_name |          0
     revenue |     13,346    29808.75    42680.09          0     485651
      ebitda |     10,353    5460.739    8671.517     -13595      82487
  rd_expense |      5,629    2099.578    2818.713     .05687      28837
advertisin~e |      6,281    765.7837    1072.822       .001   11541.87
-------------+---------------------------------------------------------
  net_income |     13,438    3141.358    6247.718     -99289      53394
        cash |     13,192     16046.1    48444.66    -.04757     331285
long_term_~t |     10,625    49249.73    144512.4    -5.9612    2944357
short_term~t |      8,184    57247.24    118859.5          0    1099811
short_term~s |      9,401    34604.06    105264.5          0     824318
-------------+---------------------------------------------------------
shareholde~y |     13,234    30338.87    53621.34     -50391     267146
  market_cap |     11,411    69433.16    86006.04     .00821   860882.5
  employment |     12,173    93562.38    174450.2          7    2300000
year_founded |     17,659    1945.101    59.14909       1727       2018
 age_of_firm |     17,659    73.89943    59.14909          1        292
-------------+---------------------------------------------------------
 global_sifi |     24,255    .0627912     .242592          0          1
primary_in~y |          0
primary_in~e |          0
gics_secto~e |          0
gics_group~e |          0
-------------+---------------------------------------------------------
gics_indus~e |          0
 gics_sector |          0
gics_indus~s |          0
revenue_gr~p |          0
      public |     24,255    .4704597    .4991369          0          1
-------------+---------------------------------------------------------
   vc_backed |     24,255    .0496392     .217203          0          1
          bs |     23,197    813884.3    450114.8        580    2377940
          fs |     23,197    782923.3    436854.3          0    2374299
    division |          0
     aw_year |     24,255    2012.409    3.707244       2001       2019
-------------+---------------------------------------------------------
        bank |     24,255     .066007    .2482995          0          1
      capmkt |     24,255    .0667079    .2495206          0          1
     consfin |     24,255    .0294785    .1691469          0          1
       insur |     24,255     .045269    .2078978          0          1
         pay |     24,255    .0985364    .2980447          0          1
-------------+---------------------------------------------------------
          it |     24,255    .3734075    .4837189          0          1
    otherind |     24,255    .4191301    .4934269          0          1
industrytype |     24,255    5.446217    1.810103          1          7
indsimplet~e |     24,255    5.005607    1.738765          1          6
      payapp |     24,255    .4392496    .4963059          0          1
-------------+---------------------------------------------------------
     bankapp |     24,255    .2261802    .4183658          0          1
    otherapp |     24,255    .4091528    .4916876          0          1
     apptype |     24,255    2.044486    .8785628          1          3
          us |     24,255    .7896104    .4075938          0          1
 othernation |     24,255    .2103896    .4075938          0          1
-------------+---------------------------------------------------------
  nationtype |     24,255     1.21039    .4075938          1          2

. sum bank-otherind if (assignee_type==2 | assignee_type==3)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        bank |     22,134    .0721063    .2586696          0          1
      capmkt |     22,134    .0731002    .2603068          0          1
     consfin |     22,134    .0322581    .1766887          0          1
       insur |     22,134    .0496069    .2171364          0          1
         pay |     22,134    .1077076    .3100178          0          1
-------------+---------------------------------------------------------
          it |     22,134    .4081504    .4915023          0          1
    otherind |     22,134    .3647782    .4813788          0          1

. 
. * Factoid mentioned in paper
. 
. sum bankapp otherapp payapp if app_year>2014

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     bankapp |      2,493    .1500201    .3571627          0          1
    otherapp |      2,493    .4640995    .4988095          0          1
      payapp |      2,493    .4328119    .4955646          0          1

. sum bankapp otherapp payapp if app_year<2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     bankapp |      5,317    .2354711    .4243328          0          1
    otherapp |      5,317    .4423547    .4967126          0          1
      payapp |      5,317     .393455    .4885622          0          1

. 
. 
. * By AppYear
. 
. drop if app_year==2018
(68 observations deleted)

. drop if indsimpletype==.
(0 observations deleted)

. sort app_year indsimpletype apptype nationtype

. egen patcount=count(patent_id), by(app_year indsimpletype apptype nationtype)

. egen patcountwt=sum(weighted_cite), by(app_year indsimpletype apptype nationtype)

. egen patcountkogan=sum(kogan_etal_val), by(app_year indsimpletype apptype nationtype)

. by app_year indsimpletype apptype nationtype: drop if _n~=1
(23,793 observations deleted)

. save temp, replace 
file temp.dta saved

. import delimited appyear_dummy2.csv, clear
(encoding automatically selected: ISO-8859-1)
(4 vars, 432 obs)

. label values indsimpletype indsimpletype1

. label values apptype apptype1

. label values nationtype nationtype1 

. merge 1:1 app_year indsimpletype apptype nationtype using temp, keepusing(patcount patcountwt patcountkogan)
(variable app_year was int, now double to accommodate using data's values)
(variable indsimpletype was byte, now float to accommodate using data's values)
(variable apptype was byte, now float to accommodate using data's values)
(variable nationtype was byte, now float to accommodate using data's values)

    Result                      Number of obs
    -----------------------------------------
    Not matched                            38
        from master                        38  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               394  (_merge==3)
    -----------------------------------------

. sum _merge

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      _merge |        432    2.824074    .5671388          1          3

. replace patcount=0 if patcount==.
(38 real changes made)

. replace patcountwt=0 if patcountwt==.
(38 real changes made)

. replace patcountkogan=0 if patcountkogan==.
(38 real changes made)

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    app_year |        432      2008.5    5.194143       2000       2017
indsimplet~e |        432         3.5    2.063943          1          6
     apptype |        432           2    .8174432          1          3
  nationtype |        432         1.5    .5005797          1          2
    patcount |        432    55.98843    80.81719          0        423
-------------+---------------------------------------------------------
  patcountwt |        432    69.81928    122.6214          0   805.9314
patcountko~n |        432    1177.929    1554.369          0    7987.16
      _merge |        432    2.824074    .5671388          1          3

. tab1 app_year indsimpletype apptype nationtype, mi nola

-> tabulation of app_year  

   app_year |      Freq.     Percent        Cum.
------------+-----------------------------------
       2000 |         24        5.56        5.56
       2001 |         24        5.56       11.11
       2002 |         24        5.56       16.67
       2003 |         24        5.56       22.22
       2004 |         24        5.56       27.78
       2005 |         24        5.56       33.33
       2006 |         24        5.56       38.89
       2007 |         24        5.56       44.44
       2008 |         24        5.56       50.00
       2009 |         24        5.56       55.56
       2010 |         24        5.56       61.11
       2011 |         24        5.56       66.67
       2012 |         24        5.56       72.22
       2013 |         24        5.56       77.78
       2014 |         24        5.56       83.33
       2015 |         24        5.56       88.89
       2016 |         24        5.56       94.44
       2017 |         24        5.56      100.00
------------+-----------------------------------
      Total |        432      100.00

-> tabulation of indsimpletype  

indsimplety |
         pe |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        108       25.00       25.00
          2 |        108       25.00       50.00
          5 |        108       25.00       75.00
          6 |        108       25.00      100.00
------------+-----------------------------------
      Total |        432      100.00

-> tabulation of apptype  

    apptype |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        144       33.33       33.33
          2 |        144       33.33       66.67
          3 |        144       33.33      100.00
------------+-----------------------------------
      Total |        432      100.00

-> tabulation of nationtype  

 nationtype |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        216       50.00       50.00
          2 |        216       50.00      100.00
------------+-----------------------------------
      Total |        432      100.00

. reg patcount app_year##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        432
                                                F(125, 306)       =       7.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8192
                                                Root MSE          =      40.78

----------------------------------------------------------------------------------------
                       |               Robust
              patcount | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              app_year |
                 2001  |  -4.416667     39.121    -0.11   0.910    -81.39688    72.56355
                 2002  |  -4.958333   37.51899    -0.13   0.895    -78.78621    68.86955
                 2003  |  -13.54167   34.64229    -0.39   0.696    -81.70891    54.62558
                 2004  |       .625   35.88221     0.02   0.986     -69.9821     71.2321
                 2005  |   2.583333   39.47019     0.07   0.948    -75.08401    80.25067
                 2006  |   19.16667   45.34984     0.42   0.673    -70.07033    108.4037
                 2007  |     28.625    49.4681     0.58   0.563    -68.71569    125.9657
                 2008  |   5.041667    43.9127     0.11   0.909    -81.36741    91.45074
                 2009  |  -2.666667   37.77291    -0.07   0.944     -76.9942    71.66086
                 2010  |   9.583333    43.9016     0.22   0.827    -76.80389    95.97056
                 2011  |      25.75   51.27121     0.50   0.616    -75.13876    126.6388
                 2012  |   50.33333   53.32063     0.94   0.346    -54.58816    155.2548
                 2013  |     21.625     51.285     0.42   0.674    -79.29088    122.5409
                 2014  |   24.66667   46.00544     0.54   0.592    -65.86038    115.1937
                 2015  |    -18.375   38.10256    -0.48   0.630    -93.35119    56.60119
                 2016  |  -64.83333   33.40663    -1.94   0.053    -130.5691    .9024579
                 2017  |  -96.54167   30.92173    -3.12   0.002    -157.3878   -35.69554
                       |
         indsimpletype |
                 Bank  |  -134.8333    27.7531    -4.86   0.000    -189.4444   -80.22226
        Other Finance  |       -128   26.94583    -4.75   0.000    -181.0226   -74.97744
             Payments  |  -136.6667   28.01906    -4.88   0.000    -191.8011   -81.53225
                       |
               apptype |
             payments  |    -18.375   18.54667    -0.99   0.323    -54.87014    18.12014
              banking  |    -31.625   20.69458    -1.53   0.128    -72.34669    9.096692
                       |
            nationtype |
                   us  |   43.41667   15.15116     2.87   0.004     13.60302    73.23031
                       |
app_year#indsimpletype |
            2001#Bank  |   4.666667   36.23504     0.13   0.898    -66.63471    75.96804
   2001#Other Finance  |   15.16667   35.02908     0.43   0.665     -53.7617    84.09503
        2001#Payments  |   7.666667    36.2377     0.21   0.833    -63.63995    78.97328
            2002#Bank  |   9.166667   34.80156     0.26   0.792    -59.31399    77.64733
   2002#Other Finance  |   17.33333   34.53673     0.50   0.616    -50.62621    85.29288
        2002#Payments  |   16.83333   34.78268     0.48   0.629    -51.61018    85.27684
            2003#Bank  |        7.5   33.64636     0.22   0.824    -58.70752    73.70752
   2003#Other Finance  |   13.83333   32.57258     0.42   0.671    -50.26126    77.92792
        2003#Payments  |       16.5   33.27302     0.50   0.620    -48.97288    81.97288
            2004#Bank  |  -1.333333   34.21393    -0.04   0.969    -68.65769    65.99102
   2004#Other Finance  |   8.833333   32.93673     0.27   0.789    -55.97782    73.64448
        2004#Payments  |   .8333333   34.30584     0.02   0.981    -66.67187    68.33853
            2005#Bank  |  -7.333333   37.90167    -0.19   0.847    -81.91423    67.24756
   2005#Other Finance  |          8   37.09611     0.22   0.829    -64.99576    80.99576
        2005#Payments  |  -4.166667    38.2271    -0.11   0.913    -79.38792    71.05459
            2006#Bank  |        -41    44.7904    -0.92   0.361    -129.1362    47.13616
   2006#Other Finance  |      -22.5     42.929    -0.52   0.601    -106.9734    61.97339
        2006#Payments  |      -35.5   44.54344    -0.80   0.426    -123.1502     52.1502
            2007#Bank  |  -44.33333    47.5261    -0.93   0.352    -137.8527      49.186
   2007#Other Finance  |  -15.16667   44.55834    -0.34   0.734    -102.8462    72.51287
        2007#Payments  |  -31.16667   46.54787    -0.67   0.504    -122.7611    60.42775
            2008#Bank  |  -16.33333   42.27975    -0.39   0.700    -99.52918    66.86252
   2008#Other Finance  |  -2.333333   40.84079    -0.06   0.954    -82.69766    78.03099
        2008#Payments  |  -17.83333    42.8143    -0.42   0.677     -102.081    66.41437
            2009#Bank  |  -6.833333   37.97726    -0.18   0.857    -81.56296    67.89629
   2009#Other Finance  |   2.333333   36.63997     0.06   0.949    -69.76486    74.43152
        2009#Payments  |         -3   38.40812    -0.08   0.938    -78.57746    72.57746
            2010#Bank  |  -26.66667    43.0553    -0.62   0.536    -111.3886    58.05526
   2010#Other Finance  |      -10.5    41.6646    -0.25   0.801    -92.48538    71.48538
        2010#Payments  |  -22.66667   44.03683    -0.51   0.607      -109.32    63.98667
            2011#Bank  |  -45.66667   50.06102    -0.91   0.362    -144.1741    52.84075
   2011#Other Finance  |  -22.16667   47.83309    -0.46   0.643    -116.2901    71.95675
        2011#Payments  |  -37.83333   49.80303    -0.76   0.448    -135.8331    60.16641
            2012#Bank  |  -69.16667   51.77993    -1.34   0.183    -171.0565    32.72312
   2012#Other Finance  |  -51.33333   50.10092    -1.02   0.306    -149.9193    47.25259
        2012#Payments  |  -61.66667   52.52031    -1.17   0.241    -165.0133    41.68001
            2013#Bank  |  -38.83333   52.26361    -0.74   0.458    -141.6749    64.00822
   2013#Other Finance  |  -30.83333   50.41973    -0.61   0.541    -130.0466    68.37992
        2013#Payments  |  -15.66667   50.56448    -0.31   0.757    -115.1648    83.83142
            2014#Bank  |  -24.33333   43.53192    -0.56   0.577    -109.9931    61.32645
   2014#Other Finance  |        -18   41.96791    -0.43   0.668    -100.5822    64.58222
        2014#Payments  |   5.666667   42.75651     0.13   0.895    -78.46732    89.80065
            2015#Bank  |   22.16667    37.5277     0.59   0.555    -51.67835    96.01168
   2015#Other Finance  |   27.83333   35.85599     0.78   0.438    -42.72217    98.38884
        2015#Payments  |   45.33333    36.8143     1.23   0.219    -27.10788    117.7745
            2016#Bank  |         80   31.39956     2.55   0.011     18.21362    141.7864
   2016#Other Finance  |   63.33333   31.16744     2.03   0.043     2.003705     124.663
        2016#Payments  |   81.16667   32.17143     2.52   0.012     17.86144    144.4719
            2017#Bank  |       91.5   29.28805     3.12   0.002     33.86853    149.1315
   2017#Other Finance  |       90.5     28.197     3.21   0.001     35.01544    145.9846
        2017#Payments  |   108.8333   29.44457     3.70   0.000     50.89387    166.7728
                       |
      app_year#apptype |
        2001#payments  |         -2   24.60488    -0.08   0.935    -50.41617    46.41617
         2001#banking  |      4.125    27.4434     0.15   0.881    -49.87665    58.12665
        2002#payments  |          1   22.64191     0.04   0.965    -43.55355    45.55355
         2002#banking  |      -.875   27.07514    -0.03   0.974    -54.15203    52.40203
        2003#payments  |     10.625   21.81972     0.49   0.627    -32.31068    53.56068
         2003#banking  |     10.625   24.70713     0.43   0.667    -37.99237    59.24237
        2004#payments  |      2.375   23.00572     0.10   0.918    -42.89443    47.64443
         2004#banking  |       6.75   25.29508     0.27   0.790    -43.02432    56.52432
        2005#payments  |       10.5   25.08125     0.42   0.676    -38.85355    59.85355
         2005#banking  |      3.625    28.6481     0.13   0.899     -52.7472     59.9972
        2006#payments  |     12.375   29.94153     0.41   0.680    -46.54235    71.29235
         2006#banking  |     15.125   31.87578     0.47   0.635    -47.59846    77.84846
        2007#payments  |      5.875   32.30215     0.18   0.856    -57.68744    69.43744
         2007#banking  |         -7    34.6487    -0.20   0.840    -75.17987    61.17987
        2008#payments  |     17.875   28.27584     0.63   0.528    -37.76469    73.51469
         2008#banking  |      4.375   31.97249     0.14   0.891    -58.53876    67.28876
        2009#payments  |     20.125   25.72313     0.78   0.435     -30.4916     70.7416
         2009#banking  |       10.5   27.07978     0.39   0.698    -42.78614    63.78614
        2010#payments  |     21.375   29.11422     0.73   0.463     -35.9144     78.6644
         2010#banking  |         10   31.11702     0.32   0.748    -51.23042    71.23042
        2011#payments  |       18.5   34.02338     0.54   0.587    -48.44939    85.44939
         2011#banking  |       -2.5   35.20437    -0.07   0.943    -71.77328    66.77328
        2012#payments  |     18.375   36.39904     0.50   0.614    -53.24909    89.99909
         2012#banking  |      -1.25   35.78057    -0.03   0.972    -71.65711    69.15711
        2013#payments  |     19.625   35.23744     0.56   0.578    -49.71336    88.96336
         2013#banking  |        -11   36.02458    -0.31   0.760    -81.88725    59.88725
        2014#payments  |        8.5   28.89892     0.29   0.769    -48.36576    65.36576
         2014#banking  |        -25   32.97337    -0.76   0.449    -89.88325    39.88325
        2015#payments  |      9.375    24.5564     0.38   0.703    -38.94578    57.69578
         2015#banking  |        -13   28.26027    -0.46   0.646    -68.60905    42.60905
        2016#payments  |      7.125   21.43327     0.33   0.740    -35.05025    49.30025
         2016#banking  |       -1.5   23.98387    -0.06   0.950    -48.69419    45.69419
        2017#payments  |     16.875   19.69805     0.86   0.392    -21.88577    55.63577
         2017#banking  |     15.375   21.90408     0.70   0.483    -27.72669    58.47669
                       |
   app_year#nationtype |
              2001#us  |  -3.916667   19.74824    -0.20   0.843    -42.77621    34.94287
              2002#us  |       -8.5   19.24666    -0.44   0.659    -46.37255    29.37255
              2003#us  |   1.916667   18.33054     0.10   0.917    -34.15319    37.98652
              2004#us  |  -1.666667   18.72843    -0.09   0.929    -38.51947    35.18614
              2005#us  |   5.083333    20.9093     0.24   0.808    -36.06088    46.22755
              2006#us  |   36.66667    24.4919     1.50   0.135    -11.52718    84.86051
              2007#us  |   50.83333   25.84549     1.97   0.050    -.0240463    101.6907
              2008#us  |   43.41667   23.43522     1.85   0.065    -2.697912    89.53125
              2009#us  |   25.58333   21.00388     1.22   0.224    -15.74698    66.91365
              2010#us  |      51.25   24.16334     2.12   0.035     3.702657    98.79734
              2011#us  |   54.83333   27.37373     2.00   0.046      .968766    108.6979
              2012#us  |   68.91667   28.53941     2.41   0.016     12.75833     125.075
              2013#us  |   48.66667   28.32821     1.72   0.087    -7.076085    104.4094
              2014#us  |         30   23.87161     1.26   0.210    -16.97328    76.97328
              2015#us  |   7.833333   20.71277     0.38   0.706    -32.92415    48.59082
              2016#us  |  -5.083333   17.60894    -0.29   0.773    -39.73327     29.5666
              2017#us  |  -21.08333   16.13167    -1.31   0.192    -52.82638    10.65971
                       |
                 _cons |   136.7917   29.51585     4.63   0.000     78.71194    194.8714
----------------------------------------------------------------------------------------

. contrast app_year##(indsimpletype apptype nationtype)

Contrasts of marginal linear predictions

Margins: asbalanced

----------------------------------------------------------
                       |         df           F        P>F
-----------------------+----------------------------------
              app_year |         17        9.10     0.0000
                       |
         indsimpletype |          3      136.91     0.0000
                       |
               apptype |          2       21.18     0.0000
                       |
            nationtype |          1      272.63     0.0000
                       |
app_year#indsimpletype |         51        2.56     0.0000
                       |
      app_year#apptype |         34        0.34     0.9998
                       |
   app_year#nationtype |         17        3.65     0.0000
                       |
           Denominator |        306
----------------------------------------------------------

. outreg2 using app_year_coeff.xls, replace noaster bdec(4) nocons bfmt(f) nose ctitle(application year)
app_year_coeff.xls
dir : seeout

. reg patcountwt app_year##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        432
                                                F(125, 306)       =       4.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6825
                                                Root MSE          =     82.001

----------------------------------------------------------------------------------------
                       |               Robust
            patcountwt | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              app_year |
                 2001  |  -46.77258   86.46363    -0.54   0.589    -216.9111    123.3659
                 2002  |  -64.98002   81.20757    -0.80   0.424    -224.7759    94.81591
                 2003  |  -72.35532    75.7847    -0.95   0.340    -221.4804    76.76979
                 2004  |  -50.32101   78.06648    -0.64   0.520    -203.9361    103.2941
                 2005  |  -56.53166   82.44524    -0.69   0.493     -218.763    105.6997
                 2006  |  -20.87111   95.74205    -0.22   0.828    -209.2672     167.525
                 2007  |   16.58607   108.6058     0.15   0.879    -197.1227    230.2948
                 2008  |  -1.642761   89.48341    -0.02   0.985    -177.7234    174.4379
                 2009  |  -50.15071   85.76975    -0.58   0.559    -218.9238    118.6224
                 2010  |  -50.35182   89.04597    -0.57   0.572    -225.5717    124.8681
                 2011  |    44.5827   124.0851     0.36   0.720    -199.5853    288.7507
                 2012  |   97.25507    131.287     0.74   0.459    -161.0845    355.5946
                 2013  |   -20.5488   88.40728    -0.23   0.816    -194.5119    153.4143
                 2014  |  -45.42858   92.78347    -0.49   0.625    -228.0029    137.1458
                 2015  |  -118.0426   81.34773    -1.45   0.148    -278.1143    42.02914
                 2016  |  -90.40154   90.76673    -1.00   0.320    -269.0075    88.20441
                 2017  |  -167.8538   70.09095    -2.39   0.017     -305.775   -29.93255
                       |
         indsimpletype |
                 Bank  |  -188.9408   60.85705    -3.10   0.002     -308.692   -69.18949
        Other Finance  |  -188.0937   60.66066    -3.10   0.002    -307.4585   -68.72886
             Payments  |   -195.538   61.66258    -3.17   0.002    -316.8744   -74.20169
                       |
               apptype |
             payments  |  -36.03492   43.91683    -0.82   0.413    -122.4521    50.38228
              banking  |    -63.117    44.7364    -1.41   0.159    -151.1469     24.9129
                       |
            nationtype |
                   us  |    83.8561   33.12841     2.53   0.012     18.66778    149.0444
                       |
app_year#indsimpletype |
            2001#Bank  |   32.03681   75.95931     0.42   0.673    -117.4319    181.5055
   2001#Other Finance  |   46.99756    74.9538     0.63   0.531    -100.4925    194.4877
        2001#Payments  |   44.44769   76.05605     0.58   0.559    -105.2114    194.1067
            2002#Bank  |   65.19606   71.58932     0.91   0.363    -75.67359    206.0657
   2002#Other Finance  |   71.78173   71.65245     1.00   0.317    -69.21215    212.7756
        2002#Payments  |   74.14894   72.41664     1.02   0.307    -68.34866    216.6465
            2003#Bank  |   52.74157   68.05838     0.77   0.439    -81.18008    186.6632
   2003#Other Finance  |   59.06337   67.77443     0.87   0.384    -74.29954    192.4263
        2003#Payments  |   69.07192   68.35869     1.01   0.313    -65.44067    203.5845
            2004#Bank  |   45.31899   70.51953     0.64   0.521    -93.44558    184.0836
   2004#Other Finance  |   62.84294   69.44408     0.90   0.366    -73.80541    199.4913
        2004#Payments  |    52.3472   71.20087     0.74   0.463    -87.75808    192.4525
            2005#Bank  |   36.89822   76.13453     0.48   0.628    -112.9153    186.7117
   2005#Other Finance  |   41.16181   76.06422     0.54   0.589    -108.5133    190.8369
        2005#Payments  |   41.50602   77.41919     0.54   0.592    -110.8353    193.8474
            2006#Bank  |  -24.07196   92.08662    -0.26   0.794    -205.2751    157.1312
   2006#Other Finance  |  -5.409584   90.67999    -0.06   0.952    -183.8448    173.0257
        2006#Payments  |  -12.49849   91.97449    -0.14   0.892     -193.481     168.484
            2007#Bank  |  -56.60401   99.81802    -0.57   0.571    -253.0206    139.8126
   2007#Other Finance  |  -15.23013   96.95878    -0.16   0.875    -206.0205    175.5602
        2007#Payments  |  -27.52491   97.92454    -0.28   0.779    -220.2156    165.1658
            2008#Bank  |  -14.30267   84.78793    -0.17   0.866    -181.1438    152.5385
   2008#Other Finance  |  -3.630646   84.70562    -0.04   0.966    -170.3099    163.0486
        2008#Payments  |   -5.20633   85.25014    -0.06   0.951     -172.957    162.5444
            2009#Bank  |   28.67687   84.62464     0.34   0.735     -137.843    195.1967
   2009#Other Finance  |   34.45374   84.05919     0.41   0.682    -130.9535    199.8609
        2009#Payments  |   50.06242   85.19334     0.59   0.557    -117.5765    217.7013
            2010#Bank  |   16.86661    83.7926     0.20   0.841     -148.016    181.7492
   2010#Other Finance  |   35.42003   81.94151     0.43   0.666    -125.8201    196.6602
        2010#Payments  |   40.65602   83.60573     0.49   0.627    -123.8589    205.1709
            2011#Bank  |  -76.41767   113.9525    -0.67   0.503    -300.6473    147.8119
   2011#Other Finance  |   -50.9121   111.5063    -0.46   0.648    -270.3282     168.504
        2011#Payments  |  -41.95478   111.4922    -0.38   0.707    -261.3431    177.4335
            2012#Bank  |  -126.9564   116.0713    -1.09   0.275    -355.3553    101.4425
   2012#Other Finance  |  -107.2773   113.0045    -0.95   0.343    -329.6416    115.0869
        2012#Payments  |  -87.78606   112.7422    -0.78   0.437    -309.6341     134.062
            2013#Bank  |  -33.37925   89.71935    -0.37   0.710    -209.9242    143.1657
   2013#Other Finance  |   36.12829   85.91036     0.42   0.674    -132.9215    205.1781
        2013#Payments  |   14.48096   86.60358     0.17   0.867     -155.933    184.8949
            2014#Bank  |   12.82216   86.28156     0.15   0.882    -156.9581    182.6024
   2014#Other Finance  |   74.88785   80.81994     0.93   0.355    -84.14533     233.921
        2014#Payments  |    81.8525   84.88952     0.96   0.336    -85.18857    248.8936
            2015#Bank  |   63.08858   73.35473     0.86   0.390    -81.25495    207.4321
   2015#Other Finance  |    216.859   90.23697     2.40   0.017     39.29546    394.4225
        2015#Payments  |   118.5403   72.98735     1.62   0.105    -25.08033    262.1609
            2016#Bank  |   85.89588   78.77178     1.09   0.276    -69.10702    240.8988
   2016#Other Finance  |   88.48343   79.12806     1.12   0.264    -67.22055    244.1874
        2016#Payments  |   111.6718   79.58393     1.40   0.162    -44.92921    268.2728
            2017#Bank  |   141.0874   62.01228     2.28   0.024     19.06299    263.1119
   2017#Other Finance  |   170.0461    64.3968     2.64   0.009     43.32946    296.7627
        2017#Payments  |   167.6936   63.63536     2.64   0.009     42.47532    292.9119
                       |
      app_year#apptype |
        2001#payments  |   13.05765   54.76289     0.24   0.812    -94.70185    120.8172
         2001#banking  |    27.5857   56.19148     0.49   0.624    -82.98489    138.1563
        2002#payments  |   10.08439   51.87764     0.19   0.846    -91.99766    112.1664
         2002#banking  |   18.15159   53.64211     0.34   0.735     -87.4025    123.7057
        2003#payments  |   34.18765   48.65543     0.70   0.483    -61.55393    129.9292
         2003#banking  |   43.91138   49.80466     0.88   0.379    -54.09158    141.9143
        2004#payments  |   18.74981   50.42316     0.37   0.710    -80.47021    117.9698
         2004#banking  |   21.67256   52.00992     0.42   0.677    -80.66979    124.0149
        2005#payments  |   39.36057   54.90948     0.72   0.474    -68.68738    147.4085
         2005#banking  |    31.9173   53.57242     0.60   0.552    -73.49966    137.3342
        2006#payments  |   49.67305   66.48545     0.75   0.456    -81.15348    180.4996
         2006#banking  |   32.45745   60.92204     0.53   0.595     -87.4217    152.3366
        2007#payments  |   20.17108   71.47708     0.28   0.778    -120.4777    160.8199
         2007#banking  |    6.90439   70.13175     0.10   0.922    -131.0971    144.9059
        2008#payments  |   31.60292   59.66835     0.53   0.597    -85.80929    149.0151
         2008#banking  |   4.126368   59.93452     0.07   0.945    -113.8096    122.0623
        2009#payments  |   42.71451   61.27972     0.70   0.486    -77.86847    163.2975
         2009#banking  |   17.31488   54.61574     0.32   0.751    -90.15506    124.7848
        2010#payments  |   50.86031   60.23839     0.84   0.399    -67.67358    169.3942
         2010#banking  |   20.24206   56.91685     0.36   0.722    -91.75588      132.24
        2011#payments  |   19.56948   80.56221     0.24   0.808    -138.9565    178.0955
         2011#banking  |  -30.19916   80.50971    -0.38   0.708    -188.6219    128.2236
        2012#payments  |   4.153788    83.0594     0.05   0.960    -159.2861    167.5937
         2012#banking  |  -31.28574   81.82705    -0.38   0.702    -192.3007    129.7292
        2013#payments  |   26.75596   65.06739     0.41   0.681    -101.2802    154.7921
         2013#banking  |   14.75056   60.03565     0.25   0.806    -103.3844    132.8855
        2014#payments  |   19.50684   62.88402     0.31   0.757     -104.233    143.2467
         2014#banking  |  -15.97886   62.41505    -0.26   0.798    -138.7959    106.8381
        2015#payments  |   .8883255    61.9361     0.01   0.989    -120.9862    122.7629
         2015#banking  |   39.79091   70.31595     0.57   0.572    -98.57307    178.1549
        2016#payments  |    10.5468   57.99731     0.18   0.856    -103.5772    124.6708
         2016#banking  |   16.71106   59.46631     0.28   0.779    -100.3036    133.7257
        2017#payments  |    43.8337    45.9881     0.95   0.341    -46.65923    134.3266
         2017#banking  |    68.2515   47.59528     1.43   0.153    -25.40396     161.907
                       |
   app_year#nationtype |
              2001#us  |  -13.15564   41.10277    -0.32   0.749    -94.03549     67.7242
              2002#us  |  -19.11876   39.08167    -0.49   0.625     -96.0216    57.78407
              2003#us  |  -17.93844   37.12897    -0.48   0.629    -90.99885    55.12197
              2004#us  |  -22.58603   38.34187    -0.59   0.556    -98.03312    52.86107
              2005#us  |  -12.35575   41.60431    -0.30   0.767    -94.22249    69.51099
              2006#us  |   31.04062   49.86642     0.62   0.534    -67.08386    129.1651
              2007#us  |   55.40723   53.70034     1.03   0.303    -50.26144    161.0759
              2008#us  |    39.0632   46.30317     0.84   0.400    -52.04971    130.1761
              2009#us  |   16.53683   45.93204     0.36   0.719    -73.84579    106.9194
              2010#us  |   32.13225   45.34961     0.71   0.479    -57.10429    121.3688
              2011#us  |   94.27725   61.16099     1.54   0.124    -26.07209    214.6266
              2012#us  |   98.48647   62.02304     1.59   0.113    -23.55916    220.5321
              2013#us  |    70.3573    49.8329     1.41   0.159    -27.70123    168.4158
              2014#us  |   62.22469   47.92206     1.30   0.195    -32.07378    156.5232
              2015#us  |    65.5203   52.48232     1.25   0.213    -37.75161    168.7922
              2016#us  |  -13.08047     43.098    -0.30   0.762    -97.88643    71.72549
              2017#us  |  -49.74485   35.72207    -1.39   0.165    -120.0368    20.54713
                       |
                 _cons |   194.3404   68.51183     2.84   0.005     59.52644    329.1543
----------------------------------------------------------------------------------------

. contrast app_year##(indsimpletype apptype nationtype)

Contrasts of marginal linear predictions

Margins: asbalanced

----------------------------------------------------------
                       |         df           F        P>F
-----------------------+----------------------------------
              app_year |         17        3.02     0.0001
                       |
         indsimpletype |          3       52.59     0.0000
                       |
               apptype |          2       14.04     0.0000
                       |
            nationtype |          1      183.98     0.0000
                       |
app_year#indsimpletype |         51        1.42     0.0383
                       |
      app_year#apptype |         34        0.44     0.9973
                       |
   app_year#nationtype |         17        2.27     0.0031
                       |
           Denominator |        306
----------------------------------------------------------

. outreg2 using app_year_wt_coeff.xls, replace noaster bdec(4) nocons bfmt(f) nose ctitle(application year)
app_year_wt_coeff.xls
dir : seeout

. reg patcountkogan app_year##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        432
                                                F(125, 306)       =       7.59
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7017
                                                Root MSE          =     1007.6

----------------------------------------------------------------------------------------
                       |               Robust
         patcountkogan | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              app_year |
                 2001  |  -586.3261   574.0857    -1.02   0.308    -1715.981    543.3291
                 2002  |   -470.128   498.2915    -0.94   0.346    -1450.639    510.3835
                 2003  |  -616.0697   473.4108    -1.30   0.194    -1547.622    315.4828
                 2004  |  -350.5881   444.6163    -0.79   0.431     -1225.48    524.3042
                 2005  |   -583.914    516.315    -1.13   0.259    -1599.891    432.0631
                 2006  |  -938.5405   746.1272    -1.26   0.209     -2406.73    529.6489
                 2007  |  -581.3875   629.2785    -0.92   0.356    -1819.648    656.8732
                 2008  |  -549.4766   606.5404    -0.91   0.366    -1742.994    644.0412
                 2009  |  -598.9825   451.4191    -1.33   0.186    -1487.261     289.296
                 2010  |  -652.3374   576.4493    -1.13   0.259    -1786.644    481.9688
                 2011  |  -179.9243   340.4974    -0.53   0.598    -849.9368    490.0883
                 2012  |   37.11203   484.5304     0.08   0.939    -916.3211    990.5451
                 2013  |  -165.5152   431.4569    -0.38   0.702    -1014.513    683.4827
                 2014  |   449.6002   449.3489     1.00   0.318    -434.6046    1333.805
                 2015  |   42.89984   361.2362     0.12   0.906    -667.9216    753.7213
                 2016  |  -444.6352   490.3133    -0.91   0.365    -1409.448    520.1773
                 2017  |  -300.9302    303.449    -0.99   0.322     -898.041    296.1806
                       |
         indsimpletype |
                 Bank  |   523.6183   360.0802     1.45   0.147    -184.9284    1232.165
        Other Finance  |  -202.5777    196.626    -1.03   0.304    -589.4879    184.3325
             Payments  |  -774.9718   319.9275    -2.42   0.016    -1404.508   -145.4354
                       |
               apptype |
             payments  |  -126.9328   302.2342    -0.42   0.675    -721.6531    467.7875
              banking  |  -212.8037   321.7857    -0.66   0.509    -845.9966    420.3891
                       |
            nationtype |
                   us  |   1386.464   249.0382     5.57   0.000     896.4196    1876.508
                       |
app_year#indsimpletype |
            2001#Bank  |    334.113   837.7886     0.40   0.690    -1314.443    1982.669
   2001#Other Finance  |   2240.049   619.3515     3.62   0.000     1021.322    3458.776
        2001#Payments  |   363.7258   602.5533     0.60   0.547    -821.9465    1549.398
            2002#Bank  |    398.679   737.6491     0.54   0.589    -1052.828    1850.186
   2002#Other Finance  |   1174.962   547.9742     2.14   0.033     96.68751    2253.236
        2002#Payments  |   540.7429   522.1024     1.04   0.301    -486.6224    1568.108
            2003#Bank  |   1052.078   709.3399     1.48   0.139    -343.7232    2447.879
   2003#Other Finance  |   806.6822    486.101     1.66   0.098    -149.8415    1763.206
        2003#Payments  |   530.8888   553.7569     0.96   0.338    -558.7646    1620.542
            2004#Bank  |   328.7546   626.5955     0.52   0.600    -904.2267    1561.736
   2004#Other Finance  |   1020.244   463.9168     2.20   0.029     107.3735    1933.115
        2004#Payments  |   272.6045   525.6406     0.52   0.604     -761.723    1306.932
            2005#Bank  |   501.2011   638.2394     0.79   0.433    -754.6925    1757.095
   2005#Other Finance  |   1097.993   566.2653     1.94   0.053     -16.2734     2212.26
        2005#Payments  |   123.3655   578.0856     0.21   0.831    -1014.161    1260.892
            2006#Bank  |   993.0332   1278.149     0.78   0.438    -1522.041    3508.107
   2006#Other Finance  |  -.9697561   469.7026    -0.00   0.998    -925.2255     923.286
        2006#Payments  |   10.98741   663.5106     0.02   0.987    -1294.633    1316.608
            2007#Bank  |   1724.784   950.2606     1.82   0.070    -145.0877    3594.657
   2007#Other Finance  |   869.3259   538.2837     1.61   0.107    -189.8801    1928.532
        2007#Payments  |   1064.001   683.5297     1.56   0.121    -281.0124    2409.014
            2008#Bank  |   944.6364   955.7405     0.99   0.324    -936.0188    2825.292
   2008#Other Finance  |   11.07754   583.6878     0.02   0.985    -1137.472    1159.627
        2008#Payments  |    785.962   594.4002     1.32   0.187    -383.6671    1955.591
            2009#Bank  |   1009.858   701.3597     1.44   0.151    -370.2403    2389.956
   2009#Other Finance  |   211.4944    356.182     0.59   0.553    -489.3816    912.3704
        2009#Payments  |    1104.37   520.5908     2.12   0.035     79.97898    2128.761
            2010#Bank  |   1257.939   883.5431     1.42   0.156    -480.6499    2996.528
   2010#Other Finance  |   528.2968    406.104     1.30   0.194     -270.813    1327.407
        2010#Payments  |   1364.959   562.1871     2.43   0.016     258.7174    2471.201
            2011#Bank  |   26.79524   473.0587     0.06   0.955    -904.0644    957.6549
   2011#Other Finance  |   401.0833    341.737     1.17   0.241    -271.3685    1073.535
        2011#Payments  |   476.6054   473.3936     1.01   0.315    -454.9133    1408.124
            2012#Bank  |   330.5629   757.4617     0.44   0.663     -1159.93    1821.056
   2012#Other Finance  |   -748.224    548.118    -1.37   0.173    -1826.781    330.3334
        2012#Payments  |   442.9826   570.1551     0.78   0.438    -678.9383    1564.904
            2013#Bank  |    298.821   622.1916     0.48   0.631    -925.4944    1523.136
   2013#Other Finance  |  -301.3437   462.9736    -0.65   0.516    -1212.359    609.6712
        2013#Payments  |   1269.898    572.746     2.22   0.027     142.8791    2396.917
            2014#Bank  |   802.3195     723.78     1.11   0.269    -621.8963    2226.535
   2014#Other Finance  |  -132.5309   433.2374    -0.31   0.760    -985.0323    719.9706
        2014#Payments  |   1997.786   584.3708     3.42   0.001     847.8922     3147.68
            2015#Bank  |   90.67229   452.9696     0.20   0.841    -800.6572    982.0018
   2015#Other Finance  |   2.396024   327.5473     0.01   0.994     -642.134    646.9261
        2015#Payments  |   1572.309   571.5669     2.75   0.006     447.6102    2697.008
            2016#Bank  |   1037.812   804.5166     1.29   0.198    -545.2725    2620.897
   2016#Other Finance  |   28.87965   419.0984     0.07   0.945    -795.7998    853.5591
        2016#Payments  |   1224.079   470.2244     2.60   0.010     298.7965    2149.361
            2017#Bank  |  -394.1562   392.2893    -1.00   0.316    -1166.082    377.7697
   2017#Other Finance  |   305.0908    250.549     1.22   0.224    -187.9262    798.1077
        2017#Payments  |   1632.663   473.2325     3.45   0.001     701.4611    2563.865
                       |
      app_year#apptype |
        2001#payments  |   360.4921   660.9251     0.55   0.586    -940.0412    1661.025
         2001#banking  |  -229.4969   613.6852    -0.37   0.709    -1437.074    978.0802
        2002#payments  |   164.9862   541.9457     0.30   0.761    -901.4256    1231.398
         2002#banking  |   -288.454   586.8767    -0.49   0.623    -1443.279    866.3707
        2003#payments  |   264.0064   600.2416     0.44   0.660     -917.117     1445.13
         2003#banking  |   -64.5776   538.9344    -0.12   0.905    -1125.064    995.9089
        2004#payments  |    110.232   512.6257     0.22   0.830    -898.4855    1118.949
         2004#banking  |  -10.60579   546.3986    -0.02   0.985     -1085.78    1064.568
        2005#payments  |   548.5744   523.2012     1.05   0.295    -480.9531    1578.102
         2005#banking  |   413.8192   592.0552     0.70   0.485    -751.1956    1578.834
        2006#payments  |   1329.895   753.5546     1.76   0.079    -152.9092      2812.7
         2006#banking  |   989.2172   928.4825     1.07   0.288    -837.8012    2816.236
        2007#payments  |   215.3962   685.6249     0.31   0.754     -1133.74    1564.532
         2007#banking  |  -572.4838   684.6738    -0.84   0.404    -1919.748    774.7809
        2008#payments  |   618.2219   720.5364     0.86   0.392    -799.6112    2036.055
         2008#banking  |  -8.685077   592.8254    -0.01   0.988    -1175.215    1157.845
        2009#payments  |   369.6526   445.1443     0.83   0.407    -506.2788    1245.584
         2009#banking  |   182.6078   551.6224     0.33   0.741    -902.8453    1268.061
        2010#payments  |   494.0011    688.672     0.72   0.474    -861.1311    1849.133
         2010#banking  |  -126.1299   504.3809    -0.25   0.803    -1118.624    866.3639
        2011#payments  |   392.4713   384.2712     1.02   0.308    -363.6772     1148.62
         2011#banking  |  -34.48012   445.9034    -0.08   0.938    -911.9052    842.9449
        2012#payments  |   835.0534   640.7176     1.30   0.193    -425.7166    2095.823
         2012#banking  |  -321.1585   583.3922    -0.55   0.582    -1469.127    826.8095
        2013#payments  |   417.4725   535.7944     0.78   0.436    -636.8352     1471.78
         2013#banking  |   -433.858   539.5098    -0.80   0.422    -1495.477    627.7607
        2014#payments  |  -211.4671    574.804    -0.37   0.713    -1342.536    919.6016
         2014#banking  |  -1457.629    614.374    -2.37   0.018    -2666.562   -248.6967
        2015#payments  |  -59.18857   433.3768    -0.14   0.891    -911.9644    793.5873
         2015#banking  |  -554.4901    479.512    -1.16   0.248    -1498.048    389.0679
        2016#payments  |   225.0378   622.4923     0.36   0.718    -999.8695    1449.945
         2016#banking  |  -309.1022   544.4136    -0.57   0.571     -1380.37     762.166
        2017#payments  |   81.55931     379.63     0.21   0.830    -665.4563     828.575
         2017#banking  |   -133.632   379.4327    -0.35   0.725    -880.2593    612.9954
                       |
   app_year#nationtype |
              2001#us  |   570.2677   558.0021     1.02   0.308    -527.7391    1668.274
              2002#us  |   467.6748   483.0639     0.97   0.334    -482.8726    1418.222
              2003#us  |   590.4934   466.5108     1.27   0.207    -327.4817    1508.469
              2004#us  |   438.3886   427.4721     1.03   0.306    -402.7682    1279.545
              2005#us  |   414.4159   467.5372     0.89   0.376    -505.5789    1334.411
              2006#us  |   845.1815   717.3683     1.18   0.240    -566.4177    2256.781
              2007#us  |   1556.881   557.0949     2.79   0.006     460.6596    2653.103
              2008#us  |   1294.669   574.4232     2.25   0.025     164.3499    2424.989
              2009#us  |   439.0762   433.0569     1.01   0.311    -413.0701    1291.223
              2010#us  |   603.7678   516.7789     1.17   0.244    -413.1222    1620.658
              2011#us  |   445.2781   349.8932     1.27   0.204    -243.2232    1133.779
              2012#us  |   1888.549   507.9368     3.72   0.000     889.0584     2888.04
              2013#us  |   982.5329   449.5083     2.19   0.030     98.01447    1867.051
              2014#us  |   541.1151   479.3743     1.13   0.260    -402.1721    1484.402
              2015#us  |  -119.2162   367.7262    -0.32   0.746    -842.8081    604.3758
              2016#us  |   27.32954   470.9851     0.06   0.954    -899.4498    954.1089
              2017#us  |  -869.0075   308.7084    -2.81   0.005    -1476.467   -261.5475
                       |
                 _cons |   272.9318   227.4458     1.20   0.231    -174.6241    720.4876
----------------------------------------------------------------------------------------

. contrast app_year##(indsimpletype apptype nationtype)

Contrasts of marginal linear predictions

Margins: asbalanced

----------------------------------------------------------
                       |         df           F        P>F
-----------------------+----------------------------------
              app_year |         17        5.76     0.0000
                       |
         indsimpletype |          3       17.94     0.0000
                       |
               apptype |          2       11.20     0.0000
                       |
            nationtype |          1      403.93     0.0000
                       |
app_year#indsimpletype |         51        2.40     0.0000
                       |
      app_year#apptype |         34        0.61     0.9591
                       |
   app_year#nationtype |         17        4.35     0.0000
                       |
           Denominator |        306
----------------------------------------------------------

. outreg2 using app_year_kogan_coeff.xls, replace noaster bdec(4) nocons bfmt(f) nose ctitle(application year)
app_year_kogan_coeff.xls
dir : seeout

. 
. * By AwYear; basic is Figures 7-A and A-6; Table A-7 
. 
. use financial_patent_data_temp, clear

. sort aw_year indsimpletype apptype nationtype

. egen patcount=count(patent_id), by(aw_year indsimpletype apptype nationtype)

. egen patcountwt=sum(weighted_cite), by(aw_year indsimpletype apptype nationtype)

. egen patcountkogan=sum(kogan_etal_val), by(aw_year indsimpletype apptype nationtype)

. by aw_year indsimpletype apptype nationtype: drop if _n~=1
(23,887 observations deleted)

. save temp, replace 
file temp.dta saved

. import delimited awyear_dummy2.csv, clear
(encoding automatically selected: ISO-8859-1)
(4 vars, 456 obs)

. label values indsimpletype indsimpletype1

. label values apptype apptype1

. label values nationtype nationtype1 

. merge 1:1 aw_year indsimpletype apptype nationtype using temp, keepusing(patcount patcountwt patcountkogan)
(variable aw_year was int, now float to accommodate using data's values)
(variable indsimpletype was byte, now float to accommodate using data's values)
(variable apptype was byte, now float to accommodate using data's values)
(variable nationtype was byte, now float to accommodate using data's values)

    Result                      Number of obs
    -----------------------------------------
    Not matched                            88
        from master                        88  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               368  (_merge==3)
    -----------------------------------------

. sum _merge

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      _merge |        456    2.614035    .7901456          1          3

. replace patcount=0 if patcount==.
(88 real changes made)

. replace patcountwt=0 if patcountwt==.
(88 real changes made)

. replace patcountkogan=0 if patcountkogan==.
(88 real changes made)

. drop if indsimpletype==.
(0 observations deleted)

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     aw_year |        456        2010    5.483241       2001       2019
indsimplet~e |        456         3.5    2.063817          1          6
     apptype |        456           2    .8173933          1          3
  nationtype |        456         1.5    .5005491          1          2
    patcount |        456    53.19079    94.64414          0        537
-------------+---------------------------------------------------------
  patcountwt |        456    66.43816    138.2212          0   1008.326
patcountko~n |        456    1116.713    1958.826          0   12113.91
      _merge |        456    2.614035    .7901456          1          3

. tab1 aw_year indsimpletype apptype nationtype, mi nola

-> tabulation of aw_year  

    aw_year |      Freq.     Percent        Cum.
------------+-----------------------------------
       2001 |         24        5.26        5.26
       2002 |         24        5.26       10.53
       2003 |         24        5.26       15.79
       2004 |         24        5.26       21.05
       2005 |         24        5.26       26.32
       2006 |         24        5.26       31.58
       2007 |         24        5.26       36.84
       2008 |         24        5.26       42.11
       2009 |         24        5.26       47.37
       2010 |         24        5.26       52.63
       2011 |         24        5.26       57.89
       2012 |         24        5.26       63.16
       2013 |         24        5.26       68.42
       2014 |         24        5.26       73.68
       2015 |         24        5.26       78.95
       2016 |         24        5.26       84.21
       2017 |         24        5.26       89.47
       2018 |         24        5.26       94.74
       2019 |         24        5.26      100.00
------------+-----------------------------------
      Total |        456      100.00

-> tabulation of indsimpletype  

indsimplety |
         pe |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        114       25.00       25.00
          2 |        114       25.00       50.00
          5 |        114       25.00       75.00
          6 |        114       25.00      100.00
------------+-----------------------------------
      Total |        456      100.00

-> tabulation of apptype  

    apptype |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        152       33.33       33.33
          2 |        152       33.33       66.67
          3 |        152       33.33      100.00
------------+-----------------------------------
      Total |        456      100.00

-> tabulation of nationtype  

 nationtype |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        228       50.00       50.00
          2 |        228       50.00      100.00
------------+-----------------------------------
      Total |        456      100.00

. reg patcount aw_year##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        456
                                                F(132, 323)       =      11.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8417
                                                Root MSE          =     44.696

---------------------------------------------------------------------------------------
                      |               Robust
             patcount | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
              aw_year |
                2002  |   7.791667   3.857884     2.02   0.044     .2019133    15.38142
                2003  |      19.75   5.775925     3.42   0.001     8.386816    31.11318
                2004  |   38.08333   7.819019     4.87   0.000      22.7007    53.46597
                2005  |      54.75   11.28373     4.85   0.000     32.55112    76.94888
                2006  |   98.91667   17.45298     5.67   0.000      64.5808    133.2525
                2007  |        100   21.19201     4.72   0.000     58.30821    141.6918
                2008  |      128.5   28.71654     4.47   0.000     72.00492    184.9951
                2009  |   138.7917   29.02169     4.78   0.000     81.69627    195.8871
                2010  |   211.9167   46.56438     4.55   0.000     120.3089    303.5244
                2011  |   191.3333   39.57199     4.84   0.000     113.4819    269.1847
                2012  |   213.4167    50.0807     4.26   0.000     114.8911    311.9422
                2013  |   229.5417   53.47579     4.29   0.000     124.3368    334.7465
                2014  |   214.5417   54.10249     3.97   0.000     108.1039    320.9794
                2015  |    158.375   40.98787     3.86   0.000      77.7381    239.0119
                2016  |   144.7083   42.04792     3.44   0.001     61.98597    227.4307
                2017  |   174.4583   35.29459     4.94   0.000      105.022    243.8946
                2018  |     176.25   30.53519     5.77   0.000      116.177     236.323
                2019  |   19.83333   7.027708     2.82   0.005     6.007472    33.65919
                      |
        indsimpletype |
                Bank  |         -6   2.588152    -2.32   0.021    -11.09176   -.9082369
       Other Finance  |         -6   2.588152    -2.32   0.021    -11.09176   -.9082369
            Payments  |       -5.5   2.530694    -2.17   0.030    -10.47872   -.5212757
                      |
              apptype |
            payments  |     -2.625   1.951542    -1.35   0.180    -6.464339    1.214339
             banking  |     -2.625   1.935463    -1.36   0.176    -6.432705    1.182705
                      |
           nationtype |
                  us  |   1.916667   1.374517     1.39   0.164    -.7874699    4.620803
                      |
aw_year#indsimpletype |
           2002#Bank  |       -8.5   3.664661    -2.32   0.021    -15.70962   -1.290382
  2002#Other Finance  |  -8.666667   3.650365    -2.37   0.018    -15.84816   -1.485174
       2002#Payments  |       -8.5   3.606684    -2.36   0.019    -15.59556   -1.404442
           2003#Bank  |  -19.33333    5.56659    -3.47   0.001    -30.28468   -8.381982
  2003#Other Finance  |  -19.33333   5.587685    -3.46   0.001    -30.32618   -8.340482
       2003#Payments  |        -20   5.599078    -3.57   0.000    -31.01527   -8.984735
           2004#Bank  |  -36.33333   7.942245    -4.57   0.000    -51.95839   -20.70827
  2004#Other Finance  |  -34.33333   7.782427    -4.41   0.000    -49.64398   -19.02269
       2004#Payments  |      -35.5   7.793338    -4.56   0.000    -50.83211   -20.16789
           2005#Bank  |        -53   10.33922    -5.13   0.000    -73.34072   -32.65928
  2005#Other Finance  |  -52.33333   10.30836    -5.08   0.000    -72.61333   -32.05333
       2005#Payments  |      -51.5   9.995465    -5.15   0.000    -71.16443   -31.83557
           2006#Bank  |  -96.33333   17.37613    -5.54   0.000     -130.518   -62.14866
  2006#Other Finance  |  -92.16667   16.85419    -5.47   0.000    -125.3245   -59.00882
       2006#Payments  |  -91.16667   16.51623    -5.52   0.000    -123.6596   -58.67369
           2007#Bank  |  -95.83333   19.06053    -5.03   0.000    -133.3318   -58.33487
  2007#Other Finance  |  -86.16667    18.2997    -4.71   0.000    -122.1683   -50.16501
       2007#Payments  |        -93   18.54468    -5.01   0.000    -129.4836   -56.51639
           2008#Bank  |  -130.6667   25.53519    -5.12   0.000    -180.9029   -80.43038
  2008#Other Finance  |     -114.5   24.12962    -4.75   0.000    -161.9711   -67.02894
       2008#Payments  |  -129.1667   25.24585    -5.12   0.000    -178.8337   -79.49961
           2009#Bank  |       -149   27.93132    -5.33   0.000    -203.9503   -94.04972
  2009#Other Finance  |     -126.5   26.21876    -4.82   0.000    -178.0811   -74.91891
       2009#Payments  |  -145.8333   27.48562    -5.31   0.000    -199.9068    -91.7599
           2010#Bank  |  -235.8333   49.25813    -4.79   0.000    -332.7406   -138.9261
  2010#Other Finance  |  -193.3333   46.12611    -4.19   0.000    -284.0789   -102.5878
       2010#Payments  |  -237.6667   49.29497    -4.82   0.000    -334.6464   -140.6869
           2011#Bank  |     -215.5    39.7535    -5.42   0.000    -293.7085   -137.2915
  2011#Other Finance  |     -170.5   37.44038    -4.55   0.000    -244.1578   -96.84221
       2011#Payments  |     -217.5   40.63561    -5.35   0.000    -297.4439   -137.5561
           2012#Bank  |       -238   50.99684    -4.67   0.000    -338.3279   -137.6721
  2012#Other Finance  |  -190.8333   47.95199    -3.98   0.000     -285.171   -96.49567
       2012#Payments  |  -242.8333   52.68346    -4.61   0.000    -346.4794   -139.1873
           2013#Bank  |  -256.3333   53.76524    -4.77   0.000    -362.1076   -150.5591
  2013#Other Finance  |     -211.5   52.68663    -4.01   0.000    -315.1523   -107.8477
       2013#Payments  |  -259.8333   55.89891    -4.65   0.000    -369.8052   -149.8614
           2014#Bank  |  -239.3333   53.54506    -4.47   0.000    -344.6744   -133.9922
  2014#Other Finance  |  -200.1667   50.96002    -3.93   0.000    -300.4221   -99.91121
       2014#Payments  |     -223.5   52.08974    -4.29   0.000     -325.978    -121.022
           2015#Bank  |       -150   39.44877    -3.80   0.000     -227.609   -72.39104
  2015#Other Finance  |  -143.8333   38.57142    -3.73   0.000    -219.7163   -67.95041
       2015#Payments  |  -143.3333   38.71197    -3.70   0.000    -219.4928   -67.17389
           2016#Bank  |  -134.8333   37.91961    -3.56   0.000    -209.4339   -60.23273
  2016#Other Finance  |  -137.8333   38.58085    -3.57   0.000    -213.7348   -61.93185
       2016#Payments  |       -125   38.10866    -3.28   0.001    -199.9725   -50.02749
           2017#Bank  |     -173.5   38.90729    -4.46   0.000    -250.0437   -96.95631
  2017#Other Finance  |  -165.3333   38.24464    -4.32   0.000    -240.5734   -90.09328
       2017#Payments  |  -142.6667    37.8662    -3.77   0.000    -217.1622   -68.17115
           2018#Bank  |  -170.6667   32.64285    -5.23   0.000    -234.8861   -106.4472
  2018#Other Finance  |     -152.5    31.2129    -4.89   0.000    -213.9062   -91.09375
       2018#Payments  |  -123.1667   32.01348    -3.85   0.000    -186.1479   -60.18541
           2019#Bank  |  -21.66667   6.693451    -3.24   0.001    -34.83493   -8.498402
  2019#Other Finance  |  -19.83333   6.429736    -3.08   0.002    -32.48278   -7.183885
       2019#Payments  |      -12.5   7.319394    -1.71   0.089     -26.8997    1.899705
                      |
      aw_year#apptype |
       2002#payments  |       2.75   2.314304     1.19   0.236    -1.803013    7.303013
        2002#banking  |      -.125    2.70184    -0.05   0.963    -5.440426    5.190426
       2003#payments  |       .625   3.761787     0.17   0.868    -6.775698    8.025698
        2003#banking  |     -3.625   4.199564    -0.86   0.389    -11.88695    4.636951
       2004#payments  |  -2.20e-12   4.437267    -0.00   1.000    -8.729593    8.729593
        2004#banking  |     -9.375   5.928108    -1.58   0.115    -21.03758    2.287578
       2005#payments  |     -5.375   6.629669    -0.81   0.418    -18.41778    7.667784
        2005#banking  |     -11.25   8.146371    -1.38   0.168    -27.27665    4.776645
       2006#payments  |     -10.25   10.90149    -0.94   0.348    -31.69689    11.19689
        2006#banking  |     -24.25   12.73444    -1.90   0.058    -49.30292    .8029243
       2007#payments  |    -16.125    13.3358    -1.21   0.227    -42.36099    10.11099
        2007#banking  |    -21.875    14.5183    -1.51   0.133    -50.43736    6.687362
       2008#payments  |    -15.125   17.26989    -0.88   0.382    -49.10067    18.85067
        2008#banking  |    -25.125   19.63993    -1.28   0.202    -63.76334    13.51334
       2009#payments  |    -10.375   18.10528    -0.57   0.567    -45.99416    25.24416
        2009#banking  |     -19.75   20.68942    -0.95   0.340    -60.45303    20.95303
       2010#payments  |     -6.875   33.51403    -0.21   0.838    -72.80835    59.05835
        2010#banking  |      -26.5   32.71234    -0.81   0.418    -90.85616    37.85616
       2011#payments  |       3.25   27.56117     0.12   0.906    -50.97208    57.47208
        2011#banking  |    -20.625   28.87507    -0.71   0.476    -77.43196    36.18196
       2012#payments  |          2   36.38749     0.05   0.956    -69.58641    73.58641
        2012#banking  |     -32.75   35.17564    -0.93   0.353    -101.9523    36.45228
       2013#payments  |      8.125   38.07139     0.21   0.831    -66.77421    83.02421
        2013#banking  |        -29   37.73342    -0.77   0.443    -103.2343    45.23429
       2014#payments  |      3.875   37.25557     0.10   0.917    -69.41921    77.16921
        2014#banking  |     -39.25   37.25292    -1.05   0.293     -112.539      34.039
       2015#payments  |    -16.125    25.7733    -0.63   0.532    -66.82974    34.57974
        2015#banking  |    -51.875    30.1518    -1.72   0.086    -111.1937    7.443703
       2016#payments  |    -14.375   26.34383    -0.55   0.586    -66.20215    37.45215
        2016#banking  |        -53     29.779    -1.78   0.076    -111.5853    5.585279
       2017#payments  |     -3.875   25.53769    -0.15   0.879    -54.11621    46.36621
        2017#banking  |    -58.625   27.28319    -2.15   0.032    -112.3002   -4.949817
       2018#payments  |    -11.125   22.34207    -0.50   0.619    -55.07935    32.82935
        2018#banking  |    -69.625   25.80746    -2.70   0.007    -120.3969   -18.85307
       2019#payments  |          4   5.411215     0.74   0.460    -6.645676    14.64568
        2019#banking  |      -8.25   5.438324    -1.52   0.130    -18.94901    2.449008
                      |
   aw_year#nationtype |
             2002#us  |  -6.17e-13   1.970161    -0.00   1.000    -3.875969    3.875969
             2003#us  |   2.833333    3.02306     0.94   0.349    -3.114039    8.780706
             2004#us  |   4.416667    4.28246     1.03   0.303    -4.008369     12.8417
             2005#us  |   9.916667   5.593932     1.77   0.077    -1.088475    20.92181
             2006#us  |       25.5   9.364662     2.72   0.007     7.076567    43.92343
             2007#us  |         25   10.30269     2.43   0.016     4.731151    45.26885
             2008#us  |   43.16667   13.68393     3.15   0.002     16.24578    70.08755
             2009#us  |   58.83333   15.19645     3.87   0.000     28.93681    88.72986
             2010#us  |   118.0833   27.27288     4.33   0.000     64.42842    171.7382
             2011#us  |   110.5833   22.64149     4.88   0.000     66.03993    155.1267
             2012#us  |        130   28.72627     4.53   0.000     73.48579    186.5142
             2013#us  |      159.5    30.9265     5.16   0.000     98.65719    220.3428
             2014#us  |   132.1667   29.30328     4.51   0.000     74.51728    189.8161
             2015#us  |   59.58333   21.24981     2.80   0.005     17.77783    101.3888
             2016#us  |   62.16667   20.97799     2.96   0.003     20.89592    103.4374
             2017#us  |   83.08333   21.74887     3.82   0.000       40.296    125.8707
             2018#us  |   95.66667   20.07645     4.77   0.000     56.16956    135.1638
             2019#us  |   13.83333   4.358055     3.17   0.002     5.259576    22.40709
                      |
                _cons |   6.791667   2.998246     2.27   0.024     .8931099    12.69022
---------------------------------------------------------------------------------------

. contrast aw_year##(indsimpletype apptype nationtype) 

Contrasts of marginal linear predictions

Margins: asbalanced

---------------------------------------------------------
                      |         df           F        P>F
----------------------+----------------------------------
              aw_year |         18       34.47     0.0000
                      |
        indsimpletype |          3      110.82     0.0000
                      |
              apptype |          2       17.00     0.0000
                      |
           nationtype |          1      216.67     0.0000
                      |
aw_year#indsimpletype |         54        6.43     0.0000
                      |
      aw_year#apptype |         36        1.37     0.0808
                      |
   aw_year#nationtype |         18       11.45     0.0000
                      |
          Denominator |        323
---------------------------------------------------------

. outreg2 using aw_year_coeff.xls, replace noaster bdec(4) nocons bfmt(f) nose ctitle(award year)
aw_year_coeff.xls
dir : seeout

. reg patcountwt aw_year##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        456
                                                F(132, 323)       =       4.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7155
                                                Root MSE          =       87.5

---------------------------------------------------------------------------------------
                      |               Robust
           patcountwt | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
              aw_year |
                2002  |   3.993205   11.97969     0.33   0.739    -19.57487    27.56128
                2003  |   17.38823   15.96178     1.09   0.277    -14.01396    48.79041
                2004  |   31.76889   16.64505     1.91   0.057    -.9775109    64.51529
                2005  |   54.05727   26.87443     2.01   0.045     1.186256    106.9283
                2006  |   112.7658   34.74534     3.25   0.001     44.41001    181.1215
                2007  |   94.87768   39.60139     2.40   0.017     16.96846    172.7869
                2008  |    141.641   55.15055     2.57   0.011     33.14131    250.1406
                2009  |   162.0967   52.80628     3.07   0.002     58.20901    265.9844
                2010  |   225.7909   90.52481     2.49   0.013     47.69818    403.8836
                2011  |   202.1671   87.94042     2.30   0.022      29.1588    375.1755
                2012  |   279.5824   98.46525     2.84   0.005     85.86821    473.2966
                2013  |   318.0764   105.7186     3.01   0.003     110.0924    526.0604
                2014  |   301.8008   127.8032     2.36   0.019     50.36892    553.2326
                2015  |   181.4073   86.39748     2.10   0.037     11.43444    351.3801
                2016  |   170.9426   60.33899     2.83   0.005     52.23555    289.6496
                2017  |   137.7775   64.12381     2.15   0.032     11.62441    263.9305
                2018  |   111.6399   63.51822     1.76   0.080     -13.3218    236.6015
                2019  |   29.55681   20.06778     1.47   0.142    -9.923261    69.03687
                      |
        indsimpletype |
                Bank  |  -10.96639   7.771449    -1.41   0.159    -26.25543    4.322661
       Other Finance  |  -10.96639   7.771449    -1.41   0.159    -26.25543    4.322661
            Payments  |  -10.46456   7.719018    -1.36   0.176    -25.65046    4.721334
                      |
              apptype |
            payments  |   -6.31719   5.915753    -1.07   0.286    -17.95546    5.321082
             banking  |  -6.082992   5.843941    -1.04   0.299    -17.57998       5.414
                      |
           nationtype |
                  us  |    5.27725    4.08913     1.29   0.198     -2.76744    13.32194
                      |
aw_year#indsimpletype |
           2002#Bank  |  -5.263368   10.03918    -0.52   0.600     -25.0138    14.48706
  2002#Other Finance  |  -5.468643   10.03751    -0.54   0.586    -25.21579    14.27851
       2002#Payments  |  -5.365526   9.994922    -0.54   0.592    -25.02889    14.29784
           2003#Bank  |   -15.1902   13.62894    -1.11   0.266     -42.0029    11.62251
  2003#Other Finance  |  -18.18438   13.97894    -1.30   0.194    -45.68565    9.316881
       2003#Payments  |  -18.55902   13.95631    -1.33   0.185    -46.01577    8.897722
           2004#Bank  |  -31.77197    15.5439    -2.04   0.042    -62.35203    -1.19191
  2004#Other Finance  |  -30.80166   15.41843    -2.00   0.047    -61.13489   -.4684341
       2004#Payments  |  -32.03325   15.50145    -2.07   0.040    -62.52981   -1.536682
           2005#Bank  |   -51.9121   22.83164    -2.27   0.024     -96.8296   -6.994604
  2005#Other Finance  |   -52.9012   22.86687    -2.31   0.021    -97.88802   -7.914382
       2005#Payments  |  -49.23636   22.27583    -2.21   0.028    -93.06039   -5.412334
           2006#Bank  |  -117.9927   35.13002    -3.36   0.001    -187.1053    -48.8802
  2006#Other Finance  |  -113.5675   34.73464    -3.27   0.001    -181.9022   -45.23282
       2006#Payments  |  -111.9408    34.2326    -3.27   0.001    -179.2879   -44.59383
           2007#Bank  |  -95.74956   34.70228    -2.76   0.006    -164.0206   -27.47854
  2007#Other Finance  |  -84.24572   32.90907    -2.56   0.011    -148.9889   -19.50254
       2007#Payments  |  -93.99214   34.02607    -2.76   0.006    -160.9328   -27.05144
           2008#Bank  |  -151.6341   47.12471    -3.22   0.001    -244.3442   -58.92396
  2008#Other Finance  |   -141.617   46.25858    -3.06   0.002    -232.6232   -50.61087
       2008#Payments  |  -153.5316   47.28028    -3.25   0.001    -246.5478   -60.51542
           2009#Bank  |  -186.5802   51.86553    -3.60   0.000    -288.6171   -84.54327
  2009#Other Finance  |  -169.6214   50.39081    -3.37   0.001     -268.757   -70.48577
       2009#Payments  |  -180.4732   51.35054    -3.51   0.001    -281.4969   -79.44946
           2010#Bank  |  -261.7461   85.48805    -3.06   0.002    -429.9298   -93.56239
  2010#Other Finance  |  -241.6367   83.46317    -2.90   0.004    -405.8368   -77.43666
       2010#Payments  |  -259.0259   84.79592    -3.05   0.002    -425.8479   -92.20387
           2011#Bank  |  -263.0862   84.54207    -3.11   0.002    -429.4088   -96.76354
  2011#Other Finance  |  -215.5402   80.99297    -2.66   0.008    -374.8805    -56.1998
       2011#Payments  |   -258.617   84.55412    -3.06   0.002    -424.9634   -92.27069
           2012#Bank  |  -287.4149   93.27717    -3.08   0.002    -470.9224   -103.9074
  2012#Other Finance  |  -270.8405   93.11208    -2.91   0.004    -454.0232   -87.65776
       2012#Payments  |  -280.1715   93.23108    -3.01   0.003    -463.5883   -96.75467
           2013#Bank  |  -374.0254   122.2295    -3.06   0.002    -614.4918   -133.5589
  2013#Other Finance  |  -343.7309   120.6467    -2.85   0.005    -581.0834   -106.3783
       2013#Payments  |  -343.8637    119.493    -2.88   0.004    -578.9466   -108.7809
           2014#Bank  |  -343.5451   115.2179    -2.98   0.003    -570.2173   -116.8729
  2014#Other Finance  |  -292.6241   107.9807    -2.71   0.007    -505.0584   -80.18978
       2014#Payments  |  -304.1586   111.3897    -2.73   0.007    -523.2995   -85.01776
           2015#Bank  |   -213.848   86.50562    -2.47   0.014    -384.0336   -43.66239
  2015#Other Finance  |  -174.5906    82.7696    -2.11   0.036    -337.4262   -11.75506
       2015#Payments  |  -189.3297   82.72886    -2.29   0.023    -352.0852   -26.57429
           2016#Bank  |  -175.2656   57.47407    -3.05   0.002    -288.3363   -62.19477
  2016#Other Finance  |  -132.7526   55.50159    -2.39   0.017    -241.9428   -23.56235
       2016#Payments  |  -135.4732   53.68289    -2.52   0.012    -241.0855   -29.86094
           2017#Bank  |  -189.5817   62.98912    -3.01   0.003    -313.5024   -65.66096
  2017#Other Finance  |  -93.06612   64.63172    -1.44   0.151    -220.2184    34.08616
       2017#Payments  |  -124.9403   57.77484    -2.16   0.031    -238.6028   -11.27781
           2018#Bank  |  -164.4127   57.02349    -2.88   0.004     -276.597   -52.22837
  2018#Other Finance  |  -36.63655   69.52085    -0.53   0.599    -173.4074    100.1343
       2018#Payments  |  -76.82097   66.79972    -1.15   0.251    -208.2384     54.5965
           2019#Bank  |  -26.95533   17.68325    -1.52   0.128    -61.74423    7.833561
  2019#Other Finance  |  -11.81612   19.83911    -0.60   0.552    -50.84629    27.21406
       2019#Payments  |  -18.42136   16.81007    -1.10   0.274     -51.4924    14.64969
                      |
      aw_year#apptype |
       2002#payments  |   3.309715   7.454945     0.44   0.657    -11.35666    17.97609
        2002#banking  |   .6272806   7.598721     0.08   0.934    -14.32195    15.57652
       2003#payments  |  -.9477493   10.23003    -0.09   0.926    -21.07365    19.17815
        2003#banking  |  -6.182635   10.42713    -0.59   0.554    -26.69631    14.33104
       2004#payments  |   1.601698   10.62975     0.15   0.880     -19.3106    22.51399
        2004#banking  |  -9.864593   11.43659    -0.86   0.389     -32.3642    12.63501
       2005#payments  |   -11.0482   16.82057    -0.66   0.512     -44.1399    22.04349
        2005#banking  |  -16.10159   17.48024    -0.92   0.358    -50.49109    18.28791
       2006#payments  |  -10.76695   24.42731    -0.44   0.660    -58.82366    37.28977
        2006#banking  |   -31.1553   22.47183    -1.39   0.167    -75.36493    13.05433
       2007#payments  |  -17.60533   25.28203    -0.70   0.487    -67.34358    32.13291
        2007#banking  |  -27.12247   25.87894    -1.05   0.295    -78.03504     23.7901
       2008#payments  |  -9.227627   34.32959    -0.27   0.788    -76.76545    58.31019
        2008#banking  |  -29.87706   34.25677    -0.87   0.384    -97.27162    37.51751
       2009#payments  |   1.683396   35.71038     0.05   0.962     -68.5709     71.9377
        2009#banking  |  -26.82715   35.48581    -0.76   0.450    -96.63964    42.98534
       2010#payments  |   3.556175   61.61389     0.06   0.954     -117.659    124.7714
        2010#banking  |  -47.15615   56.02049    -0.84   0.401    -157.3673    63.05496
       2011#payments  |   29.60273   61.91253     0.48   0.633    -92.19998    151.4055
        2011#banking  |   -20.6988   54.43508    -0.38   0.704    -127.7909    86.39327
       2012#payments  |   -19.8943   67.14207    -0.30   0.767    -151.9853    112.1967
        2012#banking  |  -91.85333   66.83734    -1.37   0.170    -223.3448    39.63814
       2013#payments  |   36.98836   86.95832     0.43   0.671    -134.0878    208.0646
        2013#banking  |   -81.2154    66.8083    -1.22   0.225    -212.6498    50.21895
       2014#payments  |  -16.40052   81.80761    -0.20   0.841    -177.3435    144.5425
        2014#banking  |  -104.7343   81.74493    -1.28   0.201     -265.554    56.08537
       2015#payments  |  -5.786522   60.24877    -0.10   0.924    -124.3161     112.743
        2015#banking  |  -67.97925   56.20053    -1.21   0.227    -178.5446    42.58606
       2016#payments  |  -54.34875   41.49159    -1.31   0.191    -135.9766    27.27912
        2016#banking  |  -76.65465   41.14112    -1.86   0.063     -157.593    4.283729
       2017#payments  |  -7.210321   44.96652    -0.16   0.873    -95.67456    81.25392
        2017#banking  |    -40.157   52.22707    -0.77   0.443    -142.9052    62.59117
       2018#payments  |  -16.17443   57.59117    -0.28   0.779    -129.4756    97.12673
        2018#banking  |   -41.9707   57.79039    -0.73   0.468    -155.6638    71.72239
       2019#payments  |  -9.577945   15.20139    -0.63   0.529    -39.48419     20.3283
        2019#banking  |  -23.90668   15.80105    -1.51   0.131    -54.99264     7.17929
                      |
   aw_year#nationtype |
             2002#us  |   .3262125   5.321401     0.06   0.951    -10.14277    10.79519
             2003#us  |   8.104974   7.448554     1.09   0.277    -6.548831    22.75878
             2004#us  |   9.628924   8.305678     1.16   0.247    -6.711132    25.96898
             2005#us  |   18.85001   12.22061     1.54   0.124    -5.192034    42.89204
             2006#us  |   50.15821   19.01308     2.64   0.009     12.75309    87.56332
             2007#us  |   46.54227   18.47786     2.52   0.012     10.19012    82.89441
             2008#us  |   69.53414   25.37959     2.74   0.006     19.60397    119.4643
             2009#us  |   84.18654   28.17634     2.99   0.003     28.75422    139.6189
             2010#us  |   152.0747   46.15751     3.29   0.001     61.26735     242.882
             2011#us  |   163.0249   46.14286     3.53   0.000     72.24642    253.8034
             2012#us  |    158.895   51.20349     3.10   0.002     58.16057    259.6295
             2013#us  |   226.8266   65.67028     3.45   0.001     97.63111    356.0221
             2014#us  |   229.9375   61.79031     3.72   0.000     108.3752    351.4998
             2015#us  |   145.3896   45.90681     3.17   0.002     55.07547    235.7037
             2016#us  |   123.3486   32.47032     3.80   0.000     59.46858    187.2286
             2017#us  |   165.7432   38.86602     4.26   0.000     89.28072    242.2057
             2018#us  |     165.52   47.71344     3.47   0.001     71.65161    259.3883
             2019#us  |   17.12014   11.18495     1.53   0.127    -4.884423     39.1247
                      |
                _cons |   12.46116   9.480432     1.31   0.190    -6.190036    31.11235
---------------------------------------------------------------------------------------

. contrast aw_year##(indsimpletype apptype nationtype) 

Contrasts of marginal linear predictions

Margins: asbalanced

---------------------------------------------------------
                      |         df           F        P>F
----------------------+----------------------------------
              aw_year |         18       13.13     0.0000
                      |
        indsimpletype |          3       44.09     0.0000
                      |
              apptype |          2       11.98     0.0000
                      |
           nationtype |          1      154.51     0.0000
                      |
aw_year#indsimpletype |         54        2.28     0.0000
                      |
      aw_year#apptype |         36        0.74     0.8677
                      |
   aw_year#nationtype |         18        7.63     0.0000
                      |
          Denominator |        323
---------------------------------------------------------

. outreg2 using aw_year_wt_coeff.xls, replace noaster bdec(4) nocons bfmt(f) nose ctitle(award year)
aw_year_wt_coeff.xls
dir : seeout

. reg patcountkogan aw_year##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        456
                                                F(125, 323)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7501
                                                Root MSE          =     1162.2

---------------------------------------------------------------------------------------
                      |               Robust
        patcountkogan | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
              aw_year |
                2002  |   10.32339   23.22312     0.44   0.657    -35.36429    56.01106
                2003  |   150.4658   92.42346     1.63   0.104    -31.36213    332.2938
                2004  |   45.00273   71.61528     0.63   0.530    -95.88857     185.894
                2005  |   246.9849   93.60686     2.64   0.009      62.8288     431.141
                2006  |   263.5009   137.7958     1.91   0.057    -7.589656    534.5915
                2007  |  -125.1678   283.3398    -0.44   0.659    -682.5922    432.2567
                2008  |  -441.8516   856.8022    -0.52   0.606    -2127.469    1243.766
                2009  |  -1585.803   1158.314    -1.37   0.172    -3864.596    692.9902
                2010  |  -467.5109   550.1999    -0.85   0.396    -1549.939    614.9169
                2011  |  -1199.826   949.0083    -1.26   0.207    -3066.844    667.1922
                2012  |  -221.3863   495.2057    -0.45   0.655    -1195.622    752.8496
                2013  |  -483.2847   561.4261    -0.86   0.390    -1587.798    621.2288
                2014  |   119.3771   406.4141     0.29   0.769    -680.1758    918.9299
                2015  |   391.0247   245.3791     1.59   0.112    -91.71827    873.7676
                2016  |   376.2366   396.4534     0.95   0.343    -403.7202    1156.193
                2017  |   533.2895   461.6772     1.16   0.249    -374.9844    1441.563
                2018  |   415.1264   733.3321     0.57   0.572    -1027.584    1857.837
                2019  |  -23.07069   15.93362    -1.45   0.149    -54.41747    8.276096
                      |
        indsimpletype |
                Bank  |  -19.00308   13.03072    -1.46   0.146    -44.63887    6.632724
       Other Finance  |  -19.00308   13.03072    -1.46   0.146    -44.63887    6.632725
            Payments  |  -13.91338   12.97927    -1.07   0.285    -39.44795     11.6212
                      |
              apptype |
            payments  |  -14.69629    10.2095    -1.44   0.151    -34.78181    5.389235
             banking  |  -11.32964    9.81978    -1.15   0.249    -30.64844    7.989164
                      |
           nationtype |
                  us  |    9.21539   7.018721     1.31   0.190     -4.59279    23.02357
                      |
aw_year#indsimpletype |
           2002#Bank  |  -21.72869   26.20845    -0.83   0.408    -73.28951    29.83213
  2002#Other Finance  |  -21.72869   26.20845    -0.83   0.408    -73.28951    29.83213
       2002#Payments  |  -1.809715   32.90535    -0.05   0.956    -66.54558    62.92615
           2003#Bank  |  -135.9095   77.32755    -1.76   0.080    -288.0387    16.21973
  2003#Other Finance  |  -58.06922   101.9061    -0.57   0.569    -258.5528    142.4143
       2003#Payments  |  -125.6151    83.6216    -1.50   0.134    -290.1268    38.89668
           2004#Bank  |  -67.68961   63.55503    -1.07   0.288    -192.7237    57.34447
  2004#Other Finance  |    117.572   119.0072     0.99   0.324    -116.5552    351.6992
       2004#Payments  |  -24.16919    51.9095    -0.47   0.642    -126.2926    77.95421
           2005#Bank  |  -221.7667   81.38208    -2.73   0.007    -381.8726   -61.66088
  2005#Other Finance  |  -173.3682   88.70877    -1.95   0.052    -347.8881    1.151708
       2005#Payments  |  -74.08682   140.8627    -0.53   0.599    -351.2111    203.0375
           2006#Bank  |  -54.96882   134.2369    -0.41   0.682    -319.0578    209.1202
  2006#Other Finance  |   -18.4211   137.6851    -0.13   0.894    -289.2939    252.4517
       2006#Payments  |  -117.0256    144.623    -0.81   0.419    -401.5476    167.4964
           2007#Bank  |   182.5844   251.9178     0.72   0.469    -313.0225    678.1914
  2007#Other Finance  |   619.2264   351.2562     1.76   0.079     -71.8125    1310.265
       2007#Payments  |  -336.5011   264.5767    -1.27   0.204    -857.0123    184.0102
           2008#Bank  |    2051.22   1410.427     1.45   0.147    -723.5645    4826.004
  2008#Other Finance  |     1646.1   631.5816     2.61   0.010     403.5668    2888.633
       2008#Payments  |  -935.1408   844.3936    -1.11   0.269    -2596.346    726.0648
           2009#Bank  |   4097.053   1776.276     2.31   0.022     602.5214    7591.584
  2009#Other Finance  |   1769.393   744.6695     2.38   0.018     304.3784    3234.408
       2009#Payments  |  -553.3385   1117.348    -0.50   0.621    -2751.536    1644.859
           2010#Bank  |   2282.861    730.521     3.12   0.002     845.6813    3720.041
  2010#Other Finance  |   1086.644   415.0561     2.62   0.009     270.0898    1903.199
       2010#Payments  |  -549.3153   619.3248    -0.89   0.376    -1767.735    669.1044
           2011#Bank  |   3207.365   1438.006     2.23   0.026      378.324    6036.406
  2011#Other Finance  |   1274.087   660.9617     1.93   0.055    -26.24615    2574.421
       2011#Payments  |  -476.5787   955.6319    -0.50   0.618    -2356.627     1403.47
           2012#Bank  |   1437.574   728.8419     1.97   0.049     3.697192     2871.45
  2012#Other Finance  |   186.0728   435.3447     0.43   0.669    -670.3963    1042.542
       2012#Payments  |   -570.511   533.6469    -1.07   0.286    -1620.374    479.3516
           2013#Bank  |   2076.615   814.2751     2.55   0.011     474.6629    3678.568
  2013#Other Finance  |   706.9187   462.9013     1.53   0.128    -203.7636    1617.601
       2013#Payments  |   106.8331   604.2928     0.18   0.860    -1082.014     1295.68
           2014#Bank  |   1123.471    589.816     1.90   0.058    -36.89465    2283.837
  2014#Other Finance  |  -472.4512   443.8103    -1.06   0.288    -1345.575    400.6726
       2014#Payments  |   81.32451   475.1548     0.17   0.864    -853.4645    1016.114
           2015#Bank  |   400.8136   306.4561     1.31   0.192    -202.0883    1003.716
  2015#Other Finance  |  -475.7972   260.8167    -1.82   0.069    -988.9111    37.31676
       2015#Payments  |   338.3341   380.2608     0.89   0.374    -409.7665    1086.435
           2016#Bank  |   1313.656   738.1135     1.78   0.076    -138.4606    2765.773
  2016#Other Finance  |  -497.8316   416.9374    -1.19   0.233    -1318.087    322.4242
       2016#Payments  |   653.7061   334.9729     1.95   0.052     -5.29792     1312.71
           2017#Bank  |   1094.128   651.4287     1.68   0.094    -187.4504    2375.707
  2017#Other Finance  |  -976.1416   503.6769    -1.94   0.053    -1967.043    14.75982
       2017#Payments  |   422.5814   500.0452     0.85   0.399    -561.1753    1406.338
           2018#Bank  |    1730.88   707.5287     2.45   0.015     338.9338    3122.827
  2018#Other Finance  |  -510.9282   788.8548    -0.65   0.518     -2062.87    1041.014
       2018#Payments  |    3268.07   1235.694     2.64   0.009     837.0463    5699.094
           2019#Bank  |   19.00308   13.03072     1.46   0.146    -6.632724    44.63887
  2019#Other Finance  |   19.00308   13.03072     1.46   0.146    -6.632725    44.63887
       2019#Payments  |   13.91338   12.97927     1.07   0.285     -11.6212    39.44795
                      |
      aw_year#apptype |
       2002#payments  |  -3.822771   20.37561    -0.19   0.851    -43.90844     36.2629
        2002#banking  |   10.03946   25.14103     0.40   0.690    -39.42139    59.50031
       2003#payments  |  -72.50246   81.94143    -0.88   0.377    -233.7087    88.70382
        2003#banking  |  -134.9058   80.66959    -1.67   0.095      -293.61    23.79835
       2004#payments  |    13.1016   86.58788     0.15   0.880    -157.2458     183.449
        2004#banking  |  -149.4839   58.95449    -2.54   0.012    -265.4671   -33.50058
       2005#payments  |  -146.1449    111.074    -1.32   0.189    -364.6647    72.37488
        2005#banking  |  -174.0023   114.0469    -1.53   0.128    -398.3709    50.36634
       2006#payments  |  -130.3954   104.0608    -1.25   0.211    -335.1179     74.3271
        2006#banking  |  -451.2053   140.5314    -3.21   0.001    -727.6777   -174.7329
       2007#payments  |   243.2227   243.7563     1.00   0.319    -236.3278    722.7731
        2007#banking  |  -34.57635   262.4069    -0.13   0.895    -550.8189    481.6662
       2008#payments  |   674.4526   1095.519     0.62   0.539      -1480.8    2829.705
        2008#banking  |  -743.9766    744.326    -1.00   0.318    -2208.316    720.3623
       2009#payments  |   881.4186   1180.138     0.75   0.456    -1440.308    3203.146
        2009#banking  |   407.6656   1075.934     0.38   0.705    -1709.057    2524.388
       2010#payments  |   470.2011   593.6244     0.79   0.429    -697.6572    1638.059
        2010#banking  |  -85.79996   545.1618    -0.16   0.875    -1158.316    986.7162
       2011#payments  |   483.0305   895.9445     0.54   0.590    -1279.593    2245.654
        2011#banking  |   665.7701   1034.711     0.64   0.520    -1369.853    2701.393
       2012#payments  |   620.1682   558.9751     1.11   0.268    -479.5234     1719.86
        2012#banking  |   55.11096   483.3269     0.11   0.909    -895.7552    1005.977
       2013#payments  |   466.3592   564.0721     0.83   0.409      -643.36    1576.078
        2013#banking  |  -379.5313   547.8438    -0.69   0.489    -1457.324    698.2614
       2014#payments  |   619.7442   525.8711     1.18   0.239    -414.8208    1654.309
        2014#banking  |  -587.9334   374.2629    -1.57   0.117    -1324.234    148.3673
       2015#payments  |   78.53628   280.0595     0.28   0.779    -472.4347    629.5073
        2015#banking  |  -691.6169   372.3902    -1.86   0.064    -1424.233     40.9997
       2016#payments  |   59.47973   555.5727     0.11   0.915    -1033.518    1152.478
        2016#banking  |  -1287.658   511.7573    -2.52   0.012    -2294.457     -280.86
       2017#payments  |   8.561883   499.4799     0.02   0.986    -974.0827    991.2065
        2017#banking  |  -904.7096   544.1011    -1.66   0.097    -1975.139    165.7198
       2018#payments  |  -162.9182   849.1634    -0.19   0.848    -1833.508    1507.671
        2018#banking  |  -2125.014   861.5006    -2.47   0.014    -3819.875    -430.153
       2019#payments  |   14.69629    10.2095     1.44   0.151    -5.389235    34.78181
        2019#banking  |   11.32964    9.81978     1.15   0.249    -7.989164    30.64844
                      |
   aw_year#nationtype |
             2002#us  |   18.66615   17.58086     1.06   0.289     -15.9213    53.25361
             2003#us  |     140.49   59.34578     2.37   0.019     23.73689     257.243
             2004#us  |   262.4472   66.47312     3.95   0.000     131.6723    393.2221
             2005#us  |   247.7493    81.4926     3.04   0.003     87.42602    408.0726
             2006#us  |    804.072    97.8114     8.22   0.000     611.6441    996.4998
             2007#us  |   1185.913   220.4934     5.38   0.000     752.1285    1619.698
             2008#us  |   3351.116   826.2433     4.06   0.000     1725.618    4976.614
             2009#us  |    3691.29   985.7738     3.74   0.000     1751.942    5630.638
             2010#us  |   2810.028   472.8301     5.94   0.000     1879.813    3740.244
             2011#us  |   3642.684    838.569     4.34   0.000     1992.937    5292.431
             2012#us  |   2614.729    451.625     5.79   0.000     1726.231    3503.227
             2013#us  |   3247.535   486.4044     6.68   0.000     2290.615    4204.456
             2014#us  |   3092.934   416.4738     7.43   0.000     2273.591    3912.278
             2015#us  |    1862.41   267.8081     6.95   0.000     1335.542    2389.279
             2016#us  |   2048.769   430.9664     4.75   0.000     1200.913    2896.624
             2017#us  |    2569.45   448.6413     5.73   0.000     1686.822    3452.078
             2018#us  |   3345.756   742.1216     4.51   0.000     1885.754    4805.758
             2019#us  |   -9.21539   7.018721    -1.31   0.190    -23.02357     4.59279
                      |
                _cons |   23.07069   15.93362     1.45   0.149    -8.276096    54.41747
---------------------------------------------------------------------------------------

. contrast aw_year##(indsimpletype apptype nationtype) 

Contrasts of marginal linear predictions

Margins: asbalanced

---------------------------------------------------------
                      |         df           F        P>F
----------------------+----------------------------------
              aw_year |         18       38.12     0.0000
                      |
        indsimpletype |          3       12.86     0.0000
                      |
              apptype |          2        7.80     0.0005
                      |
           nationtype |          1      288.09     0.0000
                      |
aw_year#indsimpletype |         54        2.76     0.0000
                      |
      aw_year#apptype |         36        1.86     0.0028
                      |
   aw_year#nationtype |         18       26.75     0.0000
                      |
          Denominator |        323
---------------------------------------------------------

. outreg2 using aw_year_kogan_coeff.xls, replace noaster bdec(4) nocons bfmt(f) nose ctitle(award year)
aw_year_kogan_coeff.xls
dir : seeout

. 
. ** Diff in diff (text)
. 
. gen postcrisis=(aw_year>=2009)

. reg patcount postcrisis##(b6.indsimpletype b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        456
                                                F(13, 442)        =      29.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6727
                                                Root MSE          =     54.939

------------------------------------------------------------------------------------------
                         |               Robust
                patcount | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------------+----------------------------------------------------------------
            1.postcrisis |   114.3139   17.03897     6.71   0.000     80.82645    147.8014
                         |
           indsimpletype |
                   Bank  |        -61   8.356103    -7.30   0.000    -77.42263   -44.57737
          Other Finance  |   -56.9375   8.433557    -6.75   0.000    -73.51235   -40.36265
               Payments  |  -59.10417      8.345    -7.08   0.000    -75.50498   -42.70336
                         |
                 apptype |
               payments  |    -8.0625    5.77534    -1.40   0.163    -19.41304    3.288039
                banking  |  -14.57812   5.736104    -2.54   0.011    -25.85155   -3.304699
                         |
              nationtype |
                     us  |   15.77083   4.308072     3.66   0.000     7.303982    24.23768
                         |
postcrisis#indsimpletype |
                 1#Bank  |  -125.4242   17.16952    -7.31   0.000    -159.1683    -91.6802
        1#Other Finance  |   -104.714   17.48329    -5.99   0.000    -139.0747    -70.3533
             1#Payments  |  -116.7443   17.25266    -6.77   0.000    -150.6518   -82.83689
                         |
      postcrisis#apptype |
             1#payments  |   1.664773   11.97234     0.14   0.889    -21.86501    25.19455
              1#banking  |  -25.25142   11.64518    -2.17   0.031    -48.13823   -2.364612
                         |
   postcrisis#nationtype |
                   1#us  |   79.19129   9.366601     8.45   0.000     60.78268     97.5999
                         |
                   _cons |   62.76562   9.339933     6.72   0.000     44.40943    81.12182
------------------------------------------------------------------------------------------

. 
. ** Adding another level of interaction (Figure 7B)
. 
. gen banksame=(apptype==2 & indsimpletype==1)

. gen paysame=(apptype==1 & indsimpletype==5)

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     aw_year |        456        2010    5.483241       2001       2019
indsimplet~e |        456         3.5    2.063817          1          6
     apptype |        456           2    .8173933          1          3
  nationtype |        456         1.5    .5005491          1          2
    patcount |        456    53.19079    94.64414          0        537
-------------+---------------------------------------------------------
  patcountwt |        456    66.43816    138.2212          0   1008.326
patcountko~n |        456    1116.713    1958.826          0   12113.91
      _merge |        456    2.614035    .7901456          1          3
  postcrisis |        456    .5789474    .4942702          0          1
    banksame |        456    .0833333     .276689          0          1
-------------+---------------------------------------------------------
     paysame |        456    .0833333     .276689          0          1

. reg patcount aw_year##(b6.indsimpletype banksame paysame b3.apptype b2.nationtype), vce(r)

Linear regression                               Number of obs     =        456
                                                F(170, 285)       =       9.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8486
                                                Root MSE          =     46.525

---------------------------------------------------------------------------------------
                      |               Robust
             patcount | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
              aw_year |
                2002  |   7.690476   4.040358     1.90   0.058    -.2622525     15.6432
                2003  |   19.96429   6.187118     3.23   0.001     7.786042    32.14253
                2004  |   38.52976   7.946066     4.85   0.000     22.88934    54.17018
                2005  |   55.42262   12.01633     4.61   0.000      31.7706    79.07464
                2006  |   100.2262   18.34168     5.46   0.000     64.12385    136.3285
                2007  |   102.0476   22.46325     4.54   0.000      57.8327    146.2625
                2008  |   130.2738    31.3213     4.16   0.000     68.62338    191.9242
                2009  |   140.9405   31.16301     4.52   0.000     79.60161    202.2793
                2010  |   214.8393    49.5776     4.33   0.000     117.2546     312.424
                2011  |    194.994   42.48107     4.59   0.000     111.3776    278.6105
                2012  |   217.3095   53.75411     4.04   0.000     111.5041     323.115
                2013  |   232.3214   57.86458     4.01   0.000     118.4253    346.2176
                2014  |   219.3214   58.70534     3.74   0.000     103.7704    334.8725
                2015  |   162.8036   43.59173     3.73   0.000     77.00098    248.6062
                2016  |    149.369    45.3499     3.29   0.001     60.10581    238.6323
                2017  |   181.3393   36.31777     4.99   0.000     109.8542    252.8244
                2018  |   184.8095   31.04663     5.95   0.000     123.6997    245.9193
                2019  |   21.82143   7.037615     3.10   0.002     7.969131    35.67373
                      |
        indsimpletype |
                Bank  |       -6.5   3.113127    -2.09   0.038    -12.62764   -.3723609
       Other Finance  |         -6   2.721825    -2.20   0.028    -11.35743   -.6425696
            Payments  |         -6   2.980115    -2.01   0.045    -11.86583    -.134172
                      |
           1.banksame |        1.5    2.09728     0.72   0.475    -2.628124    5.628124
            1.paysame |        1.5   1.840423     0.82   0.416    -2.122546    5.122546
                      |
              apptype |
            payments  |         -3   2.403286    -1.25   0.213    -7.730443    1.730443
             banking  |         -3   2.327184    -1.29   0.198    -7.580649    1.580649
                      |
           nationtype |
                  us  |   1.916667   1.443215     1.33   0.185    -.9240466     4.75738
                      |
aw_year#indsimpletype |
           2002#Bank  |  -9.647619   3.744168    -2.58   0.010    -17.01735   -2.277888
  2002#Other Finance  |  -8.666667   3.740488    -2.32   0.021    -16.02915   -1.304179
       2002#Payments  |  -6.947619   4.204124    -1.65   0.100    -15.22269    1.327453
           2003#Bank  |  -20.99524   6.005489    -3.50   0.001    -32.81598   -9.174498
  2003#Other Finance  |  -19.33333    5.80255    -3.33   0.001    -30.75462   -7.912043
       2003#Payments  |  -19.19524   6.695146    -2.87   0.004    -32.37344   -6.017032
           2004#Bank  |  -40.70952    7.20112    -5.65   0.000    -54.88365    -26.5354
  2004#Other Finance  |  -34.33333     7.8492    -4.37   0.000    -49.78309   -18.88357
       2004#Payments  |  -32.90952   9.130709    -3.60   0.000     -50.8817   -14.93734
           2005#Bank  |  -56.89524   10.77553    -5.28   0.000    -78.10496   -35.68552
  2005#Other Finance  |  -52.33333   10.75983    -4.86   0.000    -73.51214   -31.15452
       2005#Payments  |  -50.29524   12.25449    -4.10   0.000    -74.41602   -26.17446
           2006#Bank  |   -103.619   18.29527    -5.66   0.000      -139.63   -67.60805
  2006#Other Finance  |  -92.16667   17.52442    -5.26   0.000    -126.6604   -57.67296
       2006#Payments  |  -89.11905   19.25873    -4.63   0.000    -127.0264   -51.21166
           2007#Bank  |  -100.7619   21.78737    -4.62   0.000    -143.6465   -57.87733
  2007#Other Finance  |  -86.16667   19.03269    -4.53   0.000    -123.6291    -48.7042
       2007#Payments  |   -96.2619   22.15415    -4.35   0.000    -139.8684   -52.65538
           2008#Bank  |  -136.6143   28.48884    -4.80   0.000    -192.6895   -80.53906
  2008#Other Finance  |     -114.5   25.37892    -4.51   0.000    -164.4539   -64.54609
       2008#Payments  |  -130.3143   31.17316    -4.18   0.000    -191.6731   -68.95546
           2009#Bank  |  -155.3143   30.81069    -5.04   0.000    -215.9597    -94.6689
  2009#Other Finance  |     -126.5   27.64039    -4.58   0.000    -180.9052    -72.0948
       2009#Payments  |  -148.1143   33.37527    -4.44   0.000    -213.8076   -82.42098
           2010#Bank  |  -245.3952   57.49968    -4.27   0.000    -358.5731   -132.2173
  2010#Other Finance  |  -193.3333   48.89547    -3.95   0.000    -289.5754   -97.09127
       2010#Payments  |  -239.7952   54.55553    -4.40   0.000    -347.1781   -132.4124
           2011#Bank  |  -227.7714   45.54963    -5.00   0.000    -317.4278   -138.1151
  2011#Other Finance  |     -170.5   39.48817    -4.32   0.000    -248.2255   -92.77453
       2011#Payments  |  -219.8714   47.98523    -4.58   0.000    -314.3218    -125.421
           2012#Bank  |  -253.1524   59.87266    -4.23   0.000    -371.0011   -135.3037
  2012#Other Finance  |  -190.8333   50.58156    -3.77   0.000    -290.3942   -91.27252
       2012#Payments  |  -243.2524   60.21096    -4.04   0.000     -361.767   -124.7378
           2013#Bank  |  -264.1429   64.06108    -4.12   0.000    -390.2357     -138.05
  2013#Other Finance  |     -211.5   56.01282    -3.78   0.000    -321.7513   -101.2487
       2013#Payments  |  -263.1429   62.87291    -4.19   0.000     -386.897   -139.3887
           2014#Bank  |  -254.6762   63.01274    -4.04   0.000    -378.7056   -130.6468
  2014#Other Finance  |  -200.1667   53.89633    -3.71   0.000     -306.252   -94.08129
       2014#Payments  |  -227.2762   58.79702    -3.87   0.000    -343.0077   -111.5447
           2015#Bank  |  -168.2238   41.90725    -4.01   0.000    -250.7108   -85.73682
  2015#Other Finance  |  -143.8333   39.97788    -3.60   0.000    -222.5227   -65.14396
       2015#Payments  |  -142.8238   46.49816    -3.07   0.002    -234.3472   -51.30043
           2016#Bank  |  -146.7381   41.57582    -3.53   0.000    -228.5727   -64.90347
  2016#Other Finance  |  -137.8333   40.39527    -3.41   0.001    -217.3443   -58.32242
       2016#Payments  |  -131.7381   45.98992    -2.86   0.004    -222.2611   -41.21509
           2017#Bank  |  -193.2952   40.43551    -4.78   0.000    -272.8854   -113.7051
  2017#Other Finance  |  -165.3333   39.72834    -4.16   0.000    -243.5315   -87.13515
       2017#Payments  |  -150.3952   41.23817    -3.65   0.000    -231.5653   -69.22522
           2018#Bank  |  -193.1857   31.66368    -6.10   0.000    -255.5101   -130.8614
  2018#Other Finance  |     -152.5   32.40752    -4.71   0.000    -216.2885   -88.71154
       2018#Payments  |  -134.8857   35.08151    -3.84   0.000    -203.9375   -65.83398
           2019#Bank  |  -25.00952   6.975761    -3.59   0.000    -38.74007   -11.27898
  2019#Other Finance  |  -19.83333   6.504219    -3.05   0.003    -32.63573   -7.030932
       2019#Payments  |  -17.10952   7.268899    -2.35   0.019    -31.41706   -2.801986
                      |
     aw_year#banksame |
              2002 1  |   3.442857   3.432675     1.00   0.317    -3.313754    10.19947
              2003 1  |   4.985714   5.068547     0.98   0.326    -4.990821    14.96225
              2004 1  |   13.12857   7.790049     1.69   0.093    -2.204757     28.4619
              2005 1  |   11.68571   10.24051     1.14   0.255    -8.470904    31.84233
              2006 1  |   21.85714   19.34299     1.13   0.259    -16.21611    59.93039
              2007 1  |   14.78571   19.81931     0.75   0.456    -24.22509    53.79652
              2008 1  |   17.84286   27.68742     0.64   0.520    -36.65491    72.34062
              2009 1  |   18.94286     33.009     0.57   0.567    -46.02951    83.91522
              2010 1  |   28.68571   60.82997     0.47   0.638     -91.0473    148.4187
              2011 1  |   36.81429   47.31282     0.78   0.437    -56.31262    129.9412
              2012 1  |   45.45714    58.4687     0.78   0.438    -69.62811    160.5424
              2013 1  |   23.42857   66.31292     0.35   0.724    -107.0966    153.9538
              2014 1  |   46.02857   62.38575     0.74   0.461    -76.76671    168.8239
              2015 1  |   54.67143   37.24164     1.47   0.143    -18.63214     127.975
              2016 1  |   35.71429   38.43148     0.93   0.354    -39.93127    111.3598
              2017 1  |   59.38571   44.39504     1.34   0.182    -27.99805    146.7695
              2018 1  |   67.55714   42.99459     1.57   0.117    -17.07009    152.1844
              2019 1  |   10.02857   8.765585     1.14   0.254    -7.224927    27.28207
                      |
      aw_year#paysame |
              2002 1  |  -4.657143   3.096408    -1.50   0.134    -10.75187    1.437587
              2003 1  |  -2.414286    5.03991    -0.48   0.632    -12.33445    7.505884
              2004 1  |  -7.771429   7.334244    -1.06   0.290    -22.20759    6.664731
              2005 1  |  -3.614286   8.350771    -0.43   0.665     -20.0513    12.82273
              2006 1  |  -6.142857   15.48002    -0.40   0.692    -36.61254    24.32682
              2007 1  |   9.785714   16.66567     0.59   0.558     -23.0177    42.58913
              2008 1  |   3.442857    23.9333     0.14   0.886    -43.66559    50.55131
              2009 1  |   6.842857   28.32981     0.24   0.809    -48.91934    62.60506
              2010 1  |   6.385714    60.3107     0.11   0.916    -112.3252    125.0966
              2011 1  |   7.114286   48.74151     0.15   0.884    -88.82473    103.0533
              2012 1  |   1.257143   63.36914     0.02   0.984    -123.4738    125.9881
              2013 1  |   9.928571    66.7163     0.15   0.882    -121.3906    141.2478
              2014 1  |   11.32857   53.66092     0.21   0.833    -94.29343    116.9506
              2015 1  |  -1.528571    33.8233    -0.05   0.964    -68.10374     65.0466
              2016 1  |   20.21429   31.76377     0.64   0.525    -42.30705    82.73563
              2017 1  |   23.18571   41.75781     0.56   0.579    -59.00712    105.3786
              2018 1  |   35.15714   43.76822     0.80   0.422    -50.99283    121.3071
              2019 1  |   13.82857   11.08156     1.25   0.213    -7.983504    35.64065
                      |
      aw_year#apptype |
       2002#payments  |   3.914286   2.867814     1.36   0.173    -1.730497    9.559068
        2002#banking  |  -.9857143   3.404519    -0.29   0.772    -7.686906    5.715477
       2003#payments  |   1.228571   4.638065     0.26   0.791    -7.900638    10.35778
        2003#banking  |  -4.871429   5.264209    -0.93   0.356    -15.23309    5.490233
       2004#payments  |   1.942857   5.464105     0.36   0.722    -8.812264    12.69798
        2004#banking  |  -12.65714   7.481944    -1.69   0.092    -27.38402    2.069737
       2005#payments  |  -4.471429   8.090958    -0.55   0.581    -20.39704    11.45419
        2005#banking  |  -14.17143   10.12815    -1.40   0.163    -34.10689    5.764037
       2006#payments  |  -8.714286   13.87251    -0.63   0.530    -36.01985    18.59128
        2006#banking  |  -29.71429   15.72061    -1.89   0.060    -60.65752    1.228945
       2007#payments  |  -18.57143   16.19256    -1.15   0.252    -50.44361    13.30076
        2007#banking  |  -25.57143   17.51949    -1.46   0.146    -60.05544    8.912587
       2008#payments  |  -15.98571   20.73841    -0.77   0.441     -56.8056    24.83417
        2008#banking  |  -29.58571   24.02611    -1.23   0.219    -76.87686    17.70543
       2009#payments  |  -12.08571   22.45275    -0.54   0.591    -56.27997    32.10854
        2009#banking  |  -24.48571   25.89788    -0.95   0.345    -75.46109    26.48966
       2010#payments  |  -8.471429   43.75869    -0.19   0.847    -94.60264    77.65978
        2010#banking  |  -33.67143   40.50905    -0.83   0.407    -113.4063    46.06344
       2011#payments  |   1.471429   34.32832     0.04   0.966    -66.09779    69.04065
        2011#banking  |  -29.82857   36.23213    -0.82   0.411    -101.1451    41.48794
       2012#payments  |   1.685714   46.29958     0.04   0.971     -89.4468    92.81822
        2012#banking  |  -44.11429   43.45776    -1.02   0.311    -129.6532     41.4246
       2013#payments  |   5.642857   50.23282     0.11   0.911    -93.23154    104.5173
        2013#banking  |  -34.85714   46.83267    -0.74   0.457    -127.0389    57.32465
       2014#payments  |   1.042857    48.3957     0.02   0.983    -94.21549    96.30121
        2014#banking  |  -50.75714   44.92299    -1.13   0.259    -139.1801    37.66579
       2015#payments  |  -15.74286   31.68597    -0.50   0.620    -78.11106    46.62535
        2015#banking  |  -65.54286   37.03687    -1.77   0.078    -138.4434    7.357656
       2016#payments  |  -19.42857   32.02627    -0.61   0.545    -82.46661    43.60947
        2016#banking  |  -61.92857   36.88828    -1.68   0.094    -134.5366    10.67946
       2017#payments  |  -9.671429   32.17314    -0.30   0.764    -72.99854    53.65568
        2017#banking  |  -73.47143   33.37281    -2.20   0.028    -139.1599   -7.782981
       2018#payments  |  -19.91429    25.3902    -0.78   0.433     -69.8904    30.06182
        2018#banking  |  -86.51429   30.31189    -2.85   0.005    -146.1779    -26.8507
       2019#payments  |   .5428571   5.440421     0.10   0.921    -10.16565    11.25136
        2019#banking  |  -10.75714    5.94495    -1.81   0.071    -22.45872    .9444358
                      |
   aw_year#nationtype |
             2002#us  |  -6.06e-13   2.004077    -0.00   1.000    -3.944669    3.944669
             2003#us  |   2.833333   3.137573     0.90   0.367    -3.342423    9.009089
             2004#us  |   4.416667   4.272171     1.03   0.302    -3.992343    12.82568
             2005#us  |   9.916667   5.790319     1.71   0.088    -1.480549    21.31388
             2006#us  |       25.5   9.666017     2.64   0.009     6.474161    44.52584
             2007#us  |         25   10.73298     2.33   0.021     3.874024    46.12598
             2008#us  |   43.16667   14.40054     3.00   0.003     14.82176    71.51158
             2009#us  |   58.83333   15.98801     3.68   0.000     27.36378    90.30289
             2010#us  |   118.0833   28.83105     4.10   0.000     61.33452    174.8321
             2011#us  |   110.5833   23.71861     4.66   0.000     63.89747    157.2692
             2012#us  |        130   30.16791     4.31   0.000     70.61981    189.3802
             2013#us  |      159.5   32.77965     4.87   0.000     94.97907    224.0209
             2014#us  |   132.1667   30.72342     4.30   0.000     71.69307    192.6403
             2015#us  |   59.58333   21.83234     2.73   0.007     16.61024    102.5564
             2016#us  |   62.16667   21.79621     2.85   0.005      19.2647    105.0686
             2017#us  |   83.08333    21.9658     3.78   0.000     39.84756    126.3191
             2018#us  |   95.66667   19.47956     4.91   0.000      57.3246    134.0087
             2019#us  |   13.83333   4.089582     3.38   0.001     5.783716    21.88295
                      |
                _cons |   7.041667   3.295645     2.14   0.033     .5547733    13.52856
---------------------------------------------------------------------------------------

. 
. 
. 
. 
. *** FINACADEMICRUN2.TXT
. 
. clear 

. 
. use all_patent_data.dta

. 
. * Produces Tables 1, 7, A-4, A-10, A-11, A-13, A-19 and Figure A-10
. 
. gen app_year=year(app_date)

. gen aw_year=year(grant_date)

. ren patent_id patent

. 
. * Merge in in the academic citations
. 
. merge 1:1 patent using cite

    Result                      Number of obs
    -----------------------------------------
    Not matched                     2,741,008
        from master                 2,739,339  (_merge==1)
        from using                      1,669  (_merge==2)

    Matched                         1,066,355  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(1,669 observations deleted)

. drop _merge

. replace cite=0 if cite==.
(2,739,339 real changes made)

. merge 1:1 patent using citetopq

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,262,433
        from master                 3,261,450  (_merge==1)
        from using                        983  (_merge==2)

    Matched                           544,244  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(983 observations deleted)

. drop _merge

. replace citetopq=0 if citetopq==.
(3,261,450 real changes made)

. merge 1:1 patent using citeeconbus

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,759,255
        from master                 3,759,206  (_merge==1)
        from using                         49  (_merge==2)

    Matched                            46,488  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(49 observations deleted)

. drop _merge

. replace citeeconbus=0 if citeeconbus==.
(3,759,206 real changes made)

. merge 1:1 patent using citeit

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,209,631
        from master                 3,208,989  (_merge==1)
        from using                        642  (_merge==2)

    Matched                           596,705  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(642 observations deleted)

. drop _merge

. replace citeit=0 if citeit==.
(3,208,989 real changes made)

. merge 1:1 patent using citeeconbustopq

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,795,886
        from master                 3,795,870  (_merge==1)
        from using                         16  (_merge==2)

    Matched                             9,824  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(16 observations deleted)

. drop _merge

. replace citeeconbustopq=0 if citeeconbustopq==.
(3,795,870 real changes made)

. merge 1:1 patent using citetop3

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,805,003
        from master                 3,805,003  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               691  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(0 observations deleted)

. drop _merge

. replace citetop3=0 if citetop3==.
(3,805,003 real changes made)

. merge 1:1 patent using citepractop3

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,805,017
        from master                 3,805,017  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               677  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(0 observations deleted)

. drop _merge

. replace citetopprac3=0 if citetopprac3==.
(3,805,017 real changes made)

. merge 1:1 patent using citeage

    Result                      Number of obs
    -----------------------------------------
    Not matched                     2,741,008
        from master                 2,739,339  (_merge==1)
        from using                      1,669  (_merge==2)

    Matched                         1,066,355  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(1,669 observations deleted)

. drop _merge

. 
. * Merging in Marco et al claim data
. 
. ren patent patent_id

. merge 1:1 patent_id using all_patent_data_ICL_ICC_Merged_Marco_V2_20200710, keepusing(pat_clm_ct pub_clm_ct pat_wrd_mi
> n pub_wrd_min  number_independent_claim_icc shortest_independen_claim_icl)

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                         3,805,694  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(0 observations deleted)

. drop _merge

. replace pat_clm_ct=number_independent_claim_icc if (pat_clm_ct==.)
(1,286,831 real changes made)

. replace pat_wrd_min=shortest_independen_claim_icl if (pat_wrd_min==.)
(1,286,898 real changes made)

. gen claim_change=pat_clm_ct-pub_clm_ct
(1,189,740 missing values generated)

. gen length_change=pat_wrd_min-pub_wrd_min
(1,192,688 missing values generated)

. drop number_independent_claim_icc shortest_independen_claim_icl

. 
. * Identifying finance patents and academic-heavy classes
. 
. merge 1:1 patent_id using financial_patent_data_v3
(variable app_year was float, now double to accommodate using data's values)

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,781,439
        from master                 3,781,439  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            24,255  (_merge==3)
    -----------------------------------------

. sum _merge

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      _merge |  3,805,694    1.012747    .1591569          1          3

. gen finpat=(_merge==3)

. drop _merge

. merge 1:1 patent_id using university_patent

    Result                      Number of obs
    -----------------------------------------
    Not matched                     3,740,310
        from master                 3,728,591  (_merge==1)
        from using                     11,719  (_merge==2)

    Matched                            77,103  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(11,719 observations deleted)

. gen univpat=(_merge==3)

. drop _merge

. ren patent_id patent

. gen primary_cpc_tr=substr(primary_cpc,1,4)
(8,078 missing values generated)

. sort primary_cpc_tr

. by primary_cpc_tr: egen cpcaccount=sum(univpat)

. save temp, replace
file temp.dta saved

. by primary_cpc_tr: drop if _n~=1
(3,805,065 observations deleted)

. sort cpcaccount

. list primary_cpc_tr cpcaccount

     +---------------------+
     | primar~r   cpcacc~t |
     |---------------------|
  1. |     D01B          0 |
  2. |     B27D          0 |
  3. |     C12F          0 |
  4. |     B25H          0 |
  5. |     A22B          0 |
     |---------------------|
  6. |     B68C          0 |
  7. |     A47K          0 |
  8. |     C12L          0 |
  9. |     D04D          0 |
 10. |     C12C          0 |
     |---------------------|
 11. |     A63K          0 |
 12. |     B42C          0 |
 13. |     B41G          0 |
 14. |     A21C          0 |
 15. |     B41B          0 |
     |---------------------|
 16. |     H05F          0 |
 17. |     D06H          0 |
 18. |     D06J          0 |
 19. |     D01H          0 |
 20. |     B31C          0 |
     |---------------------|
 21. |     A24B          0 |
 22. |     B41N          0 |
 23. |     C14B          0 |
 24. |     B27F          0 |
 25. |     B42F          0 |
     |---------------------|
 26. |     C23D          0 |
 27. |     B27H          0 |
 28. |     B44F          0 |
 29. |     B61C          0 |
 30. |     G07G          0 |
     |---------------------|
 31. |     B67C          0 |
 32. |     B23G          0 |
 33. |     B61H          0 |
 34. |     F41F          0 |
 35. |     B25C          0 |
     |---------------------|
 36. |     B61G          0 |
 37. |     C09H          0 |
 38. |     B68G          0 |
 39. |     D02H          0 |
 40. |     D21F          0 |
     |---------------------|
 41. |     F16S          0 |
 42. |     A41G          0 |
 43. |     B43M          0 |
 44. |     A41H          0 |
 45. |     B68B          0 |
     |---------------------|
 46. |     B04C          0 |
 47. |     C12G          0 |
 48. |     C10H          0 |
 49. |     G10G          0 |
 50. |     B41C          0 |
     |---------------------|
 51. |     C10F          0 |
 52. |     C23G          0 |
 53. |     B60D          0 |
 54. |     B27C          0 |
 55. |     D07B          0 |
     |---------------------|
 56. |     D01C          0 |
 57. |     B67D          0 |
 58. |     B41L          0 |
 59. |     B60M          0 |
 60. |     A47F          0 |
     |---------------------|
 61. |     D21G          0 |
 62. |     D01G          0 |
 63. |     E21C          0 |
 64. |     F17B          0 |
 65. |     B23F          0 |
     |---------------------|
 66. |     F16P          0 |
 67. |     B60F          0 |
 68. |     B62C          0 |
 69. |     B25G          0 |
 70. |     B27L          0 |
     |---------------------|
 71. |     A24F          0 |
 72. |     B21G          0 |
 73. |     C14C          0 |
 74. |     A46D          0 |
 75. |     A61P          0 |
     |---------------------|
 76. |     F21H          0 |
 77. |     A43C          0 |
 78. |     C12J          0 |
 79. |     G10B          0 |
 80. |     D03C          0 |
     |---------------------|
 81. |     B21H          0 |
 82. |     H02B          0 |
 83. |     B27G          0 |
 84. |     A23D          0 |
 85. |     B66F          0 |
     |---------------------|
 86. |     E05C          0 |
 87. |     B21K          0 |
 88. |     F23J          0 |
 89. |     D06G          0 |
 90. |     D06L          0 |
     |---------------------|
 91. |     D05C          0 |
 92. |     D21J          0 |
 93. |     F23Q          0 |
 94. |     B60P          0 |
 95. |     G03D          0 |
     |---------------------|
 96. |     A63D          0 |
 97. |     E02C          0 |
 98. |     A01L          0 |
 99. |     D03J          0 |
100. |     B27M          0 |
     |---------------------|
101. |     G16Z          0 |
102. |     B21L          0 |
103. |     B60V          0 |
104. |     G09D          0 |
105. |     F23H          0 |
     |---------------------|
106. |     G10C          0 |
107. |     A42C          0 |
108. |     F22G          0 |
109. |     B66D          0 |
110. |     C10C          0 |
     |---------------------|
111. |     G06C          0 |
112. |     B44D          0 |
113. |     G04D          0 |
114. |     B27J          0 |
115. |     A01F          0 |
     |---------------------|
116. |     A45F          0 |
117. |     B31B          0 |
118. |     A24C          0 |
119. |     B42B          0 |
120. |     C12H          0 |
     |---------------------|
121. |     F22D          1 |
122. |     B27K          1 |
123. |     B65C          1 |
124. |     G04C          1 |
125. |     A47H          1 |
     |---------------------|
126. |     A63J          1 |
127. |     D02J          1 |
128. |     A41F          1 |
129. |     G12B          1 |
130. |     B27N          1 |
     |---------------------|
131. |     B41K          1 |
132. |     B43K          1 |
133. |     A23P          1 |
134. |     B65F          1 |
135. |     F16N          1 |
     |---------------------|
136. |     F28C          1 |
137. |     D06C          1 |
138. |     D21D          1 |
139. |     A45C          1 |
140. |     C05C          1 |
     |---------------------|
141. |     C06C          1 |
142. |     F23K          1 |
143. |     F41J          1 |
144. |     C09F          1 |
145. |     B62L          1 |
     |---------------------|
146. |     C06D          1 |
147. |     D05B          1 |
148. |     B63J          1 |
149. |     D06N          1 |
150. |     C21B          1 |
     |---------------------|
151. |     E05G          1 |
152. |     D04C          1 |
153. |     D06Q          1 |
154. |     B30B          1 |
155. |     F16T          1 |
     |---------------------|
156. |     F23G          1 |
157. |     B27B          1 |
158. |     A41C          1 |
159. |     C21C          1 |
160. |     E04F          1 |
     |---------------------|
161. |     E21D          1 |
162. |     B60S          1 |
163. |     B02B          1 |
164. |     B61F          1 |
165. |     F41C          1 |
     |---------------------|
166. |     G06M          1 |
167. |     G21D          1 |
168. |     F25C          1 |
169. |     A01J          1 |
170. |     F23B          1 |
     |---------------------|
171. |     F24V          1 |
172. |     D04G          1 |
173. |     G03C          1 |
174. |     B62H          1 |
175. |     E01H          1 |
     |---------------------|
176. |     C13B          1 |
177. |     B24D          1 |
178. |     G04B          2 |
179. |     F28B          2 |
180. |     E03C          2 |
     |---------------------|
181. |     F21L          2 |
182. |     A23N          2 |
183. |     B43L          2 |
184. |     A21B          2 |
185. |     C10K          2 |
     |---------------------|
186. |     A62C          2 |
187. |     A43D          2 |
188. |     B67B          2 |
189. |     B25F          2 |
190. |     D04B          2 |
     |---------------------|
191. |     E05D          2 |
192. |     B31D          2 |
193. |     D21B          2 |
194. |     B41D          2 |
195. |     B62J          2 |
     |---------------------|
196. |     G06J          2 |
197. |     G04R          2 |
198. |     E03D          2 |
199. |     F23N          2 |
200. |     G04G          2 |
     |---------------------|
201. |     A41B          2 |
202. |     A24D          2 |
203. |     E06C          2 |
204. |     B21F          2 |
205. |     B23C          2 |
     |---------------------|
206. |     B26B          2 |
207. |     F01P          2 |
208. |     B25D          2 |
209. |     B61D          2 |
210. |     F25J          2 |
     |---------------------|
211. |     B26F          2 |
212. |     G07D          2 |
213. |     E03F          2 |
214. |     A47G          2 |
215. |     D06P          2 |
     |---------------------|
216. |     A01B          2 |
217. |     F03C          2 |
218. |     A63C          2 |
219. |     B61B          2 |
220. |     F24B          2 |
     |---------------------|
221. |     H05C          2 |
222. |     A47D          2 |
223. |     A23F          2 |
224. |     A43B          3 |
225. |     F24H          3 |
     |---------------------|
226. |     A63G          3 |
227. |     F42C          3 |
228. |     F27D          3 |
229. |     D06F          3 |
230. |     B44B          3 |
     |---------------------|
231. |     B60J          3 |
232. |     B61J          3 |
233. |     H01K          3 |
234. |     F28G          3 |
235. |     F24D          3 |
     |---------------------|
236. |     B28C          3 |
237. |     B63C          3 |
238. |     B65B          3 |
239. |     A45B          3 |
240. |     B31F          3 |
     |---------------------|
241. |     E03B          3 |
242. |     B64F          3 |
243. |     E21F          3 |
244. |     F23M          3 |
245. |     F24T          3 |
     |---------------------|
246. |     B66B          3 |
247. |     C05B          3 |
248. |     E05F          3 |
249. |     A47J          3 |
250. |     A45D          3 |
     |---------------------|
251. |     B60H          3 |
252. |     G09C          3 |
253. |     G10F          3 |
254. |     F27B          3 |
255. |     F01M          3 |
     |---------------------|
256. |     G07B          3 |
257. |     B21B          4 |
258. |     B42D          4 |
259. |     F23R          4 |
260. |     A22C          4 |
     |---------------------|
261. |     B44C          4 |
262. |     H02G          4 |
263. |     F23L          4 |
264. |     F41B          4 |
265. |     G21F          4 |
     |---------------------|
266. |     C08C          4 |
267. |     A21D          4 |
268. |     H03C          4 |
269. |     F01B          4 |
270. |     B02C          4 |
     |---------------------|
271. |     E01B          4 |
272. |     G05G          4 |
273. |     A46B          4 |
274. |     B24C          4 |
275. |     F22B          4 |
     |---------------------|
276. |     C05F          4 |
277. |     F01L          4 |
278. |     F41G          4 |
279. |     B62B          5 |
280. |     G21H          5 |
     |---------------------|
281. |     B26D          5 |
282. |     B21J          5 |
283. |     B07C          5 |
284. |     B22C          5 |
285. |     B23D          5 |
     |---------------------|
286. |     B41F          5 |
287. |     B64B          5 |
288. |     B01B          5 |
289. |     C09G          5 |
290. |     B04B          5 |
     |---------------------|
291. |     B60C          5 |
292. |     A01C          5 |
293. |     B61K          5 |
294. |     F16J          5 |
295. |     F16G          5 |
     |---------------------|
296. |     B28D          5 |
297. |     D02G          5 |
298. |     E04G          5 |
299. |     F01C          5 |
300. |     A62B          5 |
     |---------------------|
301. |     A42B          5 |
302. |     F02F          5 |
303. |     B03D          5 |
304. |     C01D          5 |
305. |     B61L          5 |
     |---------------------|
306. |     C08H          6 |
307. |     B60B          6 |
308. |     E01C          6 |
309. |     A61D          6 |
310. |     C10J          6 |
     |---------------------|
311. |     F24C          6 |
312. |     A44B          6 |
313. |     A44C          6 |
314. |     A23K          6 |
315. |     B60T          6 |
     |---------------------|
316. |     G07F          6 |
317. |     F02N          6 |
318. |     E01D          6 |
319. |     C07G          6 |
320. |     E05B          6 |
     |---------------------|
321. |     B28B          6 |
322. |     B63H          7 |
323. |     F42D          7 |
324. |     B66C          7 |
325. |     G06E          7 |
     |---------------------|
326. |     F17D          7 |
327. |     F02G          7 |
328. |     C05D          8 |
329. |     E04D          8 |
330. |     A23B          8 |
     |---------------------|
331. |     E02F          8 |
332. |     D06B          8 |
333. |     F01K          8 |
334. |     A63H          8 |
335. |     F26B          8 |
     |---------------------|
336. |     H01T          8 |
337. |     B65H          8 |
338. |     B09B          8 |
339. |     H03J          9 |
340. |     E02B          9 |
     |---------------------|
341. |     B63G          9 |
342. |     B62K          9 |
343. |     B62M          9 |
344. |     B03B          9 |
345. |     C25F          9 |
     |---------------------|
346. |     C05G          9 |
347. |     A47B          9 |
348. |     G10D          9 |
349. |     E04H          9 |
350. |     A62D          9 |
     |---------------------|
351. |     A23J          9 |
352. |     C01C          9 |
353. |     D21H         10 |
354. |     B25B         10 |
355. |     G03G         10 |
     |---------------------|
356. |     F21S         10 |
357. |     C10B         10 |
358. |     B65G         10 |
359. |     F25D         10 |
360. |     B60G         10 |
     |---------------------|
361. |     A01D         10 |
362. |     F41A         10 |
363. |     B41M         10 |
364. |     A41D         11 |
365. |     A23G         11 |
     |---------------------|
366. |     E04C         11 |
367. |     B64D         11 |
368. |     D03D         11 |
369. |     F16D         11 |
370. |     B33Y         11 |
     |---------------------|
371. |     A47C         12 |
372. |     B60Q         12 |
373. |     C22F         12 |
374. |     F16M         12 |
375. |     F16B         13 |
     |---------------------|
376. |     F23D         13 |
377. |     C13K         13 |
378. |     F04F         13 |
379. |     G09F         13 |
380. |     C11C         14 |
     |---------------------|
381. |     B21C         14 |
382. |     C01F         14 |
383. |     A23C         14 |
384. |     B60N         14 |
385. |     A47L         15 |
     |---------------------|
386. |     D21C         15 |
387. |     F15D         15 |
388. |     A01G         15 |
389. |     C09C         15 |
390. |     B07B         15 |
     |---------------------|
391. |     B63B         15 |
392. |     C25C         15 |
393. |     G01W         16 |
394. |     G21C         16 |
395. |     A61J         16 |
     |---------------------|
396. |     F17C         16 |
397. |     B05C         17 |
398. |     B23P         17 |
399. |     F02K         17 |
400. |     F02P         17 |
     |---------------------|
401. |     B29B         17 |
402. |     F23C         17 |
403. |     F15C         17 |
404. |     C23F         17 |
405. |     C03B         18 |
     |---------------------|
406. |     C11B         18 |
407. |     F03H         18 |
408. |     B23B         18 |
409. |     B21D         18 |
410. |     G01G         18 |
     |---------------------|
411. |     D04H         18 |
412. |     G02C         19 |
413. |     F21K         19 |
414. |     H04K         19 |
415. |     B65D         19 |
     |---------------------|
416. |     F16L         20 |
417. |     G21G         20 |
418. |     F03B         20 |
419. |     C11D         20 |
420. |     E02D         20 |
     |---------------------|
421. |     C21D         20 |
422. |     G07C         20 |
423. |     F24S         21 |
424. |     G16C         21 |
425. |     B60K         21 |
     |---------------------|
426. |     B64G         21 |
427. |     B22D         22 |
428. |     F03D         22 |
429. |     E04B         22 |
430. |     F04C         23 |
     |---------------------|
431. |     B23H         23 |
432. |     F02C         23 |
433. |     H01C         23 |
434. |     B09C         23 |
435. |     B60R         23 |
     |---------------------|
436. |     G08C         24 |
437. |     D06M         24 |
438. |     F24F         25 |
439. |     E06B         25 |
440. |     F42B         26 |
     |---------------------|
441. |     F01D         26 |
442. |     B08B         27 |
443. |     G04F         27 |
444. |     C22B         28 |
445. |     F15B         29 |
     |---------------------|
446. |     H01R         29 |
447. |     H02S         29 |
448. |     G06G         29 |
449. |     B24B         30 |
450. |     F16F         31 |
     |---------------------|
451. |     E01F         31 |
452. |     B23Q         31 |
453. |     C12Y         32 |
454. |     F41H         32 |
455. |     C12R         32 |
     |---------------------|
456. |     A23L         33 |
457. |     G10H         33 |
458. |     A61C         33 |
459. |     C07B         34 |
460. |     B06B         34 |
     |---------------------|
461. |     H03D         34 |
462. |     F02M         34 |
463. |     B60W         35 |
464. |     A61Q         35 |
465. |     A61G         35 |
     |---------------------|
466. |     H02H         36 |
467. |     H04H         37 |
468. |     A63F         37 |
469. |     D01D         38 |
470. |     B60L         38 |
     |---------------------|
471. |     B82B         39 |
472. |     C06B         39 |
473. |     G21B         40 |
474. |     B29D         41 |
475. |     F28D         41 |
     |---------------------|
476. |     G10K         41 |
477. |     H04S         42 |
478. |     H03G         43 |
479. |     C10L         43 |
480. |     C09J         43 |
     |---------------------|
481. |     F16H         43 |
482. |     C10M         44 |
483. |     B64C         45 |
484. |     F04D         46 |
485. |     A01M         49 |
     |---------------------|
486. |     F28F         50 |
487. |     C08B         52 |
488. |     G01H         53 |
489. |     H05G         54 |
490. |     C09B         55 |
     |---------------------|
491. |     A63B         55 |
492. |     F16C         55 |
493. |     F02B         55 |
494. |     G21K         56 |
495. |     G16H         56 |
     |---------------------|
496. |     A01H         58 |
497. |     F01N         58 |
498. |     G03B         59 |
499. |     H01H         59 |
500. |     F21V         60 |
     |---------------------|
501. |     C07J         60 |
502. |     F03G         61 |
503. |     G05F         61 |
504. |     F25B         61 |
505. |     B62D         64 |
     |---------------------|
506. |     D01F         65 |
507. |     G01F         66 |
508. |     B05B         67 |
509. |     H04M         68 |
510. |     C03C         68 |
     |---------------------|
511. |     H02P         72 |
512. |     B03C         73 |
513. |     F16K         73 |
514. |     C40B         75 |
515. |     G03H         75 |
     |---------------------|
516. |     G01D         81 |
517. |     A61H         82 |
518. |     G08B         83 |
519. |     G01P         84 |
520. |     F04B         86 |
     |---------------------|
521. |     C10G         87 |
522. |     G01M         87 |
523. |     B01F         88 |
524. |                  90 |
525. |     F02D         91 |
     |---------------------|
526. |     H05H         93 |
527. |     C01G         94 |
528. |     G01K         97 |
529. |     C25D         99 |
530. |     B81B         99 |
     |---------------------|
531. |     B41J         99 |
532. |     E21B        100 |
533. |     C25B        100 |
534. |     C08K        105 |
535. |     H02N        106 |
     |---------------------|
536. |     H03B        109 |
537. |     B22F        109 |
538. |     B05D        113 |
539. |     H04Q        114 |
540. |     H02K        114 |
     |---------------------|
541. |     G08G        121 |
542. |     C22C        122 |
543. |     B23K        123 |
544. |     G05D        124 |
545. |     H03L        131 |
     |---------------------|
546. |     G16B        140 |
547. |     C08L        142 |
548. |     H01F        142 |
549. |     C12M        145 |
550. |     G09B        146 |
     |---------------------|
551. |     G05B        160 |
552. |     C09D        164 |
553. |     H05B        165 |
554. |     G09G        171 |
555. |     C08J        172 |
     |---------------------|
556. |     G01V        174 |
557. |     B25J        177 |
558. |     H01B        182 |
559. |     G01L        182 |
560. |     G01Q        184 |
     |---------------------|
561. |     A01K        187 |
562. |     B32B        192 |
563. |     G01T        199 |
564. |     G06N        208 |
565. |     H01P        211 |
     |---------------------|
566. |     H03H        211 |
567. |     B81C        213 |
568. |     C04B        216 |
569. |     C02F        232 |
570. |     G06Q        234 |
     |---------------------|
571. |     C30B        235 |
572. |     G11B        249 |
573. |     G01C        251 |
574. |     H01G        257 |
575. |     H02J        260 |
     |---------------------|
576. |     A01N        262 |
577. |     H04R        263 |
578. |     H02M        265 |
579. |     H04J        275 |
580. |     B29C        288 |
     |---------------------|
581. |     H05K        296 |
582. |     G01B        303 |
583. |     C07H        304 |
584. |     G10L        309 |
585. |     H03F        340 |
     |---------------------|
586. |     H03K        351 |
587. |     G01J        367 |
588. |     C08F        374 |
589. |     B01L        380 |
590. |     C23C        383 |
     |---------------------|
591. |     G03F        386 |
592. |     G01S        388 |
593. |     C09K        407 |
594. |     C01B        449 |
595. |     A61M        457 |
     |---------------------|
596. |     C08G        479 |
597. |     H01Q        490 |
598. |     C07F        500 |
599. |     C12P        503 |
600. |     A61L        506 |
     |---------------------|
601. |     G11C        508 |
602. |     H03M        524 |
603. |     B01D        561 |
604. |     A61F        578 |
605. |     G02F        640 |
     |---------------------|
606. |     H01S        643 |
607. |     A61N        736 |
608. |     B01J        778 |
609. |     B82Y        856 |
610. |     C07C        883 |
     |---------------------|
611. |     H01J        926 |
612. |     G06K        955 |
613. |     G01R       1069 |
614. |     H01M       1150 |
615. |     G06T       1179 |
     |---------------------|
616. |     H04N       1251 |
617. |     H04B       1338 |
618. |     G02B       1638 |
619. |     H04W       1737 |
620. |     C12Q       1806 |
     |---------------------|
621. |     C07D       2103 |
622. |     A61B       2547 |
623. |     G06F       2745 |
624. |     H04L       2884 |
625. |     C07K       3460 |
     |---------------------|
626. |     C12N       3528 |
627. |     G01N       4911 |
628. |     H01L       4966 |
629. |     A61K       6327 |
     +---------------------+

. use temp, clear

. gen academicclass=(cpcaccount>=500)

. drop cpcaccount

. 
. * Figure A-10 and Table A-19
. 
. ttest pub_clm_ct if claim_change~=., by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2600032    2.997243    .0018623    3.002838    2.993593    3.000893
       1 |  15,922    3.598354    .0252017    3.180009    3.548956    3.647753
---------+--------------------------------------------------------------------
Combined | 2615954    3.000901    .0018575    3.004311    2.997261    3.004542
---------+--------------------------------------------------------------------
    diff |           -.6011118    .0238792               -.6479141   -.5543094
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -25.1731
H0: diff = 0                                     Degrees of freedom =  2.6e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest pat_clm_ct if claim_change~=., by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2600032     2.66251    .0011983    1.932291    2.660161    2.664859
       1 |  15,922    3.065946    .0153608    1.938259    3.035838    3.096055
---------+--------------------------------------------------------------------
Combined | 2615954    2.664965    .0011949    1.932581    2.662624    2.667307
---------+--------------------------------------------------------------------
    diff |           -.4034366    .0153606               -.4335428   -.3733304
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -26.2644
H0: diff = 0                                     Degrees of freedom =  2.6e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest pub_wrd_min if length_change~=., by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2597101    111.5161     .070509    113.6289    111.3779    111.6543
       1 |  15,905    117.5991    .7411505    93.47021    116.1463    119.0518
---------+--------------------------------------------------------------------
Combined | 2613006    111.5531    .0702255     113.518    111.4155    111.6907
---------+--------------------------------------------------------------------
    diff |            -6.08299    .9028594               -7.852563   -4.313417
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -6.7375
H0: diff = 0                                     Degrees of freedom =  2.6e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest pat_wrd_min if length_change~=., by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2597101     160.554    .0690712    111.3119    160.4186    160.6894
       1 |  15,905    201.1762     .945409    119.2303    199.3231    203.0293
---------+--------------------------------------------------------------------
Combined | 2613006    160.8013    .0689193    111.4066    160.6662    160.9364
---------+--------------------------------------------------------------------
    diff |           -40.62221    .8857174               -42.35818   -38.88623
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -45.8636
H0: diff = 0                                     Degrees of freedom =  2.6e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest claim_change, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2600032   -.3347328    .0017894    2.885298   -.3382399   -.3312257
       1 |  15,922    -.532408    .0238623    3.011001   -.5791808   -.4856352
---------+--------------------------------------------------------------------
Combined | 2615954    -.335936    .0017844     2.88612   -.3394334   -.3324385
---------+--------------------------------------------------------------------
    diff |            .1976752    .0229422                .1527093    .2426411
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   8.6162
H0: diff = 0                                     Degrees of freedom =  2.6e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest length_change, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2597101    49.03796    .0660736     106.481    48.90846    49.16746
       1 |  15,905    83.57718    .9720636    122.5918    81.67182    85.48253
---------+--------------------------------------------------------------------
Combined | 2613006    49.24819    .0659583    106.6203    49.11892    49.37747
---------+--------------------------------------------------------------------
    diff |           -34.53922    .8477364               -36.20075   -32.87769
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -40.7429
H0: diff = 0                                     Degrees of freedom =  2.6e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. by finpat, sort: tab aw_year, sum(claim_change)

------------------------------------------------------------------------------------------------------------------------
-> finpat = 0

            |       Summary of claim_change
    aw_year |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2001 |  -.93915132   2.8988525       1,249
       2002 |  -.50046745   4.0233695      29,950
       2003 |  -.32786646   3.1195647      82,131
       2004 |  -.41198692    4.313784     110,120
       2005 |  -.40179873   4.8461517     113,191
       2006 |  -.51828239   4.6260651     146,343
       2007 |  -.51436281   3.5074159     138,239
       2008 |  -.48923787   2.8930542     141,747
       2009 |  -.49569436   3.8345047     152,126
       2010 |   -.4554211   2.5867685     201,721
       2011 |  -.35382896   2.2621853     207,589
       2012 |  -.26671781   1.9842651     234,645
       2013 |  -.23445665   1.9333505     256,235
       2014 |  -.22121505   2.2389048     277,897
       2015 |  -.13167566   1.7636428     242,710
       2016 |  -.17493604   1.7871934     155,554
       2017 |  -.29358394   1.8596176      75,389
       2018 |  -.40654016    2.047123      29,510
       2019 |  -.51953337   2.3803865       3,686
------------+------------------------------------
      Total |   -.3347328   2.8852985   2,600,032

------------------------------------------------------------------------------------------------------------------------
-> finpat = 1

            |       Summary of claim_change
    aw_year |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2001 |         -.5   .70710678           2
       2002 |  -.26086957   1.7377465          23
       2003 |  -.38356164   2.3370811          73
       2004 |  -.35955056   3.6118048         178
       2005 |  -.54771784   3.4264299         241
       2006 |  -.51012891   3.5648174         543
       2007 |  -.67182131   3.4272166         582
       2008 |   -.7044586   3.2583164         785
       2009 |  -.76861966   3.1709241       1,007
       2010 |  -.92289988   4.4584481       1,738
       2011 |  -.57864524   3.2712633       1,742
       2012 |  -.41718107    2.803265       1,944
       2013 |        -.38   2.2185779       2,300
       2014 |  -.39361702   2.2902822       1,974
       2015 |  -.32082922   1.6883496       1,013
       2016 |  -.29411765   1.5153653         612
       2017 |  -.49193548   1.8282294         620
       2018 |  -.70103093   4.4106486         485
       2019 |        -.45   1.6408452          60
------------+------------------------------------
      Total |  -.53240799   3.0110007      15,922


. by finpat, sort: tab aw_year, sum(length_change)

------------------------------------------------------------------------------------------------------------------------
-> finpat = 0

            |      Summary of length_change
    aw_year |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2001 |   21.324779   63.913612       1,247
       2002 |   16.911976   101.45555      29,901
       2003 |   17.124166   129.09007      81,802
       2004 |    18.25736   148.40291     109,617
       2005 |   20.927342   140.64399     112,582
       2006 |   32.125669   116.21448     145,772
       2007 |   38.238873   116.29496     137,902
       2008 |   44.995013   101.13714     141,574
       2009 |    52.82116    105.3967     152,024
       2010 |   56.224431   102.01943     201,634
       2011 |   52.160193   90.704288     207,549
       2012 |   50.433007   90.079114     234,615
       2013 |   50.296842   87.835726     256,207
       2014 |    53.82888   86.091998     277,869
       2015 |   57.168468   103.62596     242,693
       2016 |   69.390018   107.48138     155,539
       2017 |   87.388899   107.06683      75,382
       2018 |   107.30407   115.18423      29,506
       2019 |   122.10391   120.07064       3,686
------------+------------------------------------
      Total |   49.037957     106.481   2,597,101

------------------------------------------------------------------------------------------------------------------------
-> finpat = 1

            |      Summary of length_change
    aw_year |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2001 |          20   33.941125           2
       2002 |   6.7391304   27.003733          23
       2003 |   3.8493151   104.68294          73
       2004 |   37.403409    156.0902         176
       2005 |   30.394191   130.24998         241
       2006 |   49.461967   203.99444         539
       2007 |   59.927711   108.30891         581
       2008 |   75.158163   152.87109         784
       2009 |   91.690239   117.50249       1,004
       2010 |   97.867282   117.72306       1,733
       2011 |   75.347302   117.61454       1,742
       2012 |   73.920267   119.15466       1,944
       2013 |   67.404783    100.4985       2,300
       2014 |   76.014698   92.774707       1,973
       2015 |   87.897335   103.23261       1,013
       2016 |   113.97386   110.09075         612
       2017 |   150.09677   134.28769         620
       2018 |   183.52371   139.41232         485
       2019 |   200.38333   117.43561          60
------------+------------------------------------
      Total |   83.577177   122.59183      15,905


. 
. * Repeated
. 
. by app_year, sort: sum(finpat)

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    197,509    .0053972    .0732675          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2001

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    210,886    .0053821     .073165          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2002

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    210,206    .0050141    .0706329          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2003

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    200,429    .0052887    .0725308          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2004

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    200,036     .005694    .0752435          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    203,575     .006042    .0774953          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2006

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    209,348    .0072654    .0849274          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2007

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    216,704    .0081078    .0896779          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2008

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    218,213    .0073552    .0854467          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2009

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    210,203    .0068791    .0826546          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    221,971    .0077578    .0877361          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2011

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    239,574    .0073672    .0855161          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2012

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    259,948    .0080978    .0896227          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2013

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    267,812    .0062432    .0787669          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2014

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    257,970    .0060356    .0774544          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    226,414    .0051454    .0715471          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2016

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    164,291    .0046381    .0679458          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2017

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     79,995    .0053253    .0727808          0          1

------------------------------------------------------------------------------------------------------------------------
-> app_year = 2018

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     10,610     .006409    .0798033          0          1


. by aw_year, sort: sum(finpat)

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |      1,015           0           0          0          0

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2001

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     36,632    .0010646    .0326119          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2002

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    109,984    .0008456    .0290667          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2003

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    142,614     .001199    .0346065          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2004

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    153,079    .0019206    .0437824          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    137,967    .0028847    .0536325          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2006

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    169,740    .0045069    .0669821          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2007

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    155,735    .0050406    .0708183          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2008

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    156,977    .0068354    .0823937          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2009

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    166,952    .0078286    .0881326          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    219,428    .0103633    .1012717          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2011

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    224,598    .0097864    .0984411          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2012

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    253,494    .0096452    .0977354          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2013

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    278,425    .0105199    .1020258          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2014

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    301,594    .0083324     .090901          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    299,356    .0046366    .0679348          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2016

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    304,113    .0043832    .0660609          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2017

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    319,990    .0057314    .0754891          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2018

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |    308,849    .0067768    .0820419          0          1

------------------------------------------------------------------------------------------------------------------------
-> aw_year = 2019

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
      finpat |     65,152    .0049576    .0702363          0          1


. drop app_date aw_year

. 
. * Table A-11
. 
. ttest cite, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439     3.68566    .0105544    20.52407    3.664973    3.706346
       1 |  24,255    2.325871    .0669838    10.43207    2.194579    2.457163
---------+--------------------------------------------------------------------
Combined | 3805694    3.676993     .010496    20.47579    3.656421    3.697565
---------+--------------------------------------------------------------------
    diff |            1.359789    .1318932                1.101283    1.618295
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  10.3098
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest citetopq, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439    1.534962    .0061522    11.96346    1.522904     1.54702
       1 |  24,255    .2730571     .008745    1.361944    .2559164    .2901978
---------+--------------------------------------------------------------------
Combined | 3805694    1.526919    .0061134    11.92619    1.514937    1.538901
---------+--------------------------------------------------------------------
    diff |            1.261905      .07682                 1.11134    1.412469
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  16.4268
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest citeeconbus, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439    .0180979    .0001601    .3112529    .0177842    .0184116
       1 |  24,255    .5410019    .0160911    2.506025    .5094624    .5725413
---------+--------------------------------------------------------------------
Combined | 3805694    .0214305    .0001904    .3715056    .0210573    .0218038
---------+--------------------------------------------------------------------
    diff |            -.522904     .002378               -.5275648   -.5182432
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -2.2e+02
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citeit, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439    .8246326    .0028022    5.449151    .8191404    .8301249
       1 |  24,255    1.304143    .0517611    8.061284    1.202688    1.405598
---------+--------------------------------------------------------------------
Combined | 3805694    .8276887    .0028039    5.469882    .8221932    .8331842
---------+--------------------------------------------------------------------
    diff |           -.4795108    .0352335               -.5485672   -.4104545
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -13.6095
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citeeconbustopq, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439    .0028812    .0000373    .0725281    .0028081    .0029543
       1 |  24,255    .0749948    .0034496    .5372488    .0682333    .0817564
---------+--------------------------------------------------------------------
Combined | 3805694    .0033408    .0000432     .084257    .0032561    .0034254
---------+--------------------------------------------------------------------
    diff |           -.0721137    .0005415                -.073175   -.0710524
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.3e+02
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citetop3, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439    .0000738    7.65e-06    .0148775    .0000588    .0000888
       1 |  24,255    .0430014    .0028248    .4399332    .0374647    .0485382
---------+--------------------------------------------------------------------
Combined | 3805694    .0003474    .0000196     .038276    .0003089    .0003858
---------+--------------------------------------------------------------------
    diff |           -.0429277    .0002456                -.043409   -.0424464
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.7e+02
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citetopprac3, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3781439    .0000785    5.98e-06    .0116244    .0000668    .0000903
       1 |  24,255    .0293548    .0020337    .3167293    .0253686     .033341
---------+--------------------------------------------------------------------
Combined | 3805694    .0002651    .0000143     .027911    .0002371    .0002932
---------+--------------------------------------------------------------------
    diff |           -.0292762    .0001792               -.0296274   -.0289251
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.6e+02
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citeage, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1057694    9.615724    .0072781    7.485109    9.601459    9.629989
       1 |   8,661    8.750092    .0714264    6.647266    8.610079    8.890105
---------+--------------------------------------------------------------------
Combined | 1066355    9.608693    .0072426    7.479083    9.594498    9.622888
---------+--------------------------------------------------------------------
    diff |            .8656317    .0806886                .7074849    1.023779
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  10.7281
H0: diff = 0                                     Degrees of freedom =  1.1e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest cite if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420    6.189256     .020316    27.43356    6.149437    6.229075
       1 |  24,255    2.325871    .0669838    10.43207    2.194579    2.457163
---------+--------------------------------------------------------------------
Combined | 1847675     6.13854    .0200712    27.28264    6.099201    6.177879
---------+--------------------------------------------------------------------
    diff |            3.863385    .1763189                3.517806    4.208964
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  21.9113
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest citetopq if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420    2.819001    .0122881    16.59313    2.794916    2.843085
       1 |  24,255    .2730571     .008745    1.361944    .2559164    .2901978
---------+--------------------------------------------------------------------
Combined | 1847675    2.785579    .0121292    16.48714    2.761806    2.809352
---------+--------------------------------------------------------------------
    diff |            2.545943    .1065485                2.337112    2.754775
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  23.8947
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest citeeconbus if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420    .0196707    .0001751    .2365052    .0193275     .020014
       1 |  24,255    .5410019    .0160911    2.506025    .5094624    .5725413
---------+--------------------------------------------------------------------
Combined | 1847675    .0265144    .0002764    .3757122    .0259727    .0270561
---------+--------------------------------------------------------------------
    diff |           -.5213311    .0023979                -.526031   -.5166312
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -2.2e+02
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citeit if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420    1.289398    .0048918    6.605544    1.279811    1.298986
       1 |  24,255    1.304143    .0517611    8.061284    1.202688    1.405598
---------+--------------------------------------------------------------------
Combined | 1847675    1.289592    .0048751    6.626723    1.280037    1.299147
---------+--------------------------------------------------------------------
    diff |            -.014745    .0428319               -.0986941    .0692041
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -0.3443
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.3653         Pr(|T| > |t|) = 0.7307          Pr(T > t) = 0.6347

. ttest citeeconbustopq if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420     .003477    .0000494    .0666826    .0033802    .0035738
       1 |  24,255    .0749948    .0034496    .5372488    .0682333    .0817564
---------+--------------------------------------------------------------------
Combined | 1847675    .0044158    .0000668    .0907927    .0042849    .0045467
---------+--------------------------------------------------------------------
    diff |           -.0715179    .0005845               -.0726634   -.0703723
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.2e+02
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citetop3 if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420    .0000208    3.64e-06    .0049122    .0000137     .000028
       1 |  24,255    .0430014    .0028248    .4399332    .0374647    .0485382
---------+--------------------------------------------------------------------
Combined | 1847675    .0005851    .0000374    .0508755    .0005117    .0006584
---------+--------------------------------------------------------------------
    diff |           -.0429806    .0003273               -.0436221   -.0423391
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.3e+02
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citetopprac3 if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823420    .0000384    4.91e-06    .0066236    .0000288     .000048
       1 |  24,255    .0293548    .0020337    .3167293    .0253686     .033341
---------+--------------------------------------------------------------------
Combined | 1847675    .0004232    .0000272    .0370307    .0003698    .0004766
---------+--------------------------------------------------------------------
    diff |           -.0293164    .0002384               -.0297836   -.0288492
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.2e+02
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest citeage if (academicclass==1 | finpat==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 734,060    9.247992    .0079366    6.799841    9.232437    9.263548
       1 |   8,661    8.750092    .0714264    6.647266    8.610079    8.890105
---------+--------------------------------------------------------------------
Combined | 742,721    9.242186    .0078884    6.798287    9.226725    9.257647
---------+--------------------------------------------------------------------
    diff |            .4979002    .0734767                .3538883     .641912
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   6.7763
H0: diff = 0                                     Degrees of freedom =   742719

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. 
. * Table 1
. 
. ttest weighted, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 3768208    .9983961    .0015926    3.091514    .9952747    1.001518
       1 |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
Combined | 3792460           1    .0015888    3.093975    .9968861    1.003114
---------+--------------------------------------------------------------------
    diff |           -.2508122    .0199309               -.2898761   -.2117483
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -12.5841
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1316170    11.81063    .0270669    31.05233    11.75758    11.86368
       1 |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
Combined | 1325669    12.11012    .0281724    32.43701    12.05491    12.16534
---------+--------------------------------------------------------------------
    diff |           -41.79723    .3320346                 -42.448   -41.14645
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.3e+02
H0: diff = 0                                     Degrees of freedom =  1.3e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kelly_etal_val_5, by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2673451      .80577    .0002323    .3799069    .8053146    .8062254
       1 |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
Combined | 2691606    .8061168     .000232    .3806262    .8056621    .8065715
---------+--------------------------------------------------------------------
    diff |           -.0514192    .0028343               -.0569743   -.0458641
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -18.1418
H0: diff = 0                                     Degrees of freedom =  2.7e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. 
. median weighted, by(finpat)

Median test

   Greater |
  than the |        finpat
    median |         0          1 |     Total
-----------+----------------------+----------
        no | 1,884,275     11,961 | 1,896,236 
       yes | 1,883,933     12,291 | 1,896,224 
-----------+----------------------+----------
     Total | 3,768,208     24,252 | 3,792,460 

          Pearson chi2(1) =   4.5214   Pr = 0.033

   Continuity corrected:
          Pearson chi2(1) =   4.4940   Pr = 0.034

. median kogan, by(finpat)

Median test

   Greater |
  than the |        finpat
    median |         0          1 |     Total
-----------+----------------------+----------
        no |   660,361      2,551 |   662,912 
       yes |   655,809      6,948 |   662,757 
-----------+----------------------+----------
     Total | 1,316,170      9,499 | 1,325,669 

          Pearson chi2(1) =  2.1e+03   Pr = 0.000

   Continuity corrected:
          Pearson chi2(1) =  2.1e+03   Pr = 0.000

. median kelly_etal_val_5, by(finpat)

Median test

   Greater |
  than the |        finpat
    median |         0          1 |     Total
-----------+----------------------+----------
        no | 1,337,835      7,968 | 1,345,803 
       yes | 1,335,616     10,187 | 1,345,803 
-----------+----------------------+----------
     Total | 2,673,451     18,155 | 2,691,606 

          Pearson chi2(1) = 273.0597   Pr = 0.000

   Continuity corrected:
          Pearson chi2(1) = 272.8136   Pr = 0.000

. 
. by finpat, sort: sum weighted, d

------------------------------------------------------------------------------------------------------------------------
-> finpat = 0

                        weighted_cite
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%            0              0
10%            0              0       Obs           3,768,208
25%            0              0       Sum of wgt.   3,768,208

50%     .2586888                      Mean           .9983961
                        Largest       Std. dev.      3.091514
75%     .9717713       425.5162
90%     2.378798         442.64       Variance       9.557457
95%     4.003763       471.5185       Skewness       25.82782
99%     11.08333       471.5185       Kurtosis       1842.695

------------------------------------------------------------------------------------------------------------------------
-> finpat = 1

                        weighted_cite
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%            0              0
10%            0              0       Obs              24,252
25%            0              0       Sum of wgt.      24,252

50%     .2758648                      Mean           1.249208
                        Largest       Std. dev.      3.446227
75%     1.072996       83.60576
90%     3.141883       91.45031       Variance       11.87648
95%     5.606566       93.63201       Skewness       10.18602
99%     14.66316       102.0472       Kurtosis       180.4905


. by finpat, sort: sum kogan, d

------------------------------------------------------------------------------------------------------------------------
-> finpat = 0

                       kogan_etal_val
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0137876       .0002206
 5%     .0414019       .0002206
10%     .1008019       .0002206       Obs           1,316,170
25%     .8157117       .0002219       Sum of wgt.   1,316,170

50%      4.04202                      Mean           11.81063
                        Largest       Std. dev.      31.05233
75%     11.45032       2816.691
90%     27.53065       2816.691       Variance       964.2472
95%      46.1084       5188.046       Skewness       23.35778
99%     123.7374       5199.875       Kurtosis         1942.6

------------------------------------------------------------------------------------------------------------------------
-> finpat = 1

                       kogan_etal_val
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0587895       .0006292
 5%     .3440014       .0008004
10%     1.028698       .0008913       Obs               9,499
25%      3.50696       .0010749       Sum of wgt.       9,499

50%     17.50364                      Mean           53.60786
                        Largest       Std. dev.      107.2379
75%     59.53204        1414.11
90%     135.1003       1682.365       Variance       11499.96
95%     216.7009       1780.582       Skewness       6.263092
99%     477.2724       1940.746       Kurtosis       65.96473


. by finpat, sort: sum kelly_etal_val_5, d

------------------------------------------------------------------------------------------------------------------------
-> finpat = 0

                      kelly_etal_val_5
-------------------------------------------------------------
      Percentiles      Smallest
 1%      .018569              0
 5%     .1011062              0
10%     .1985878              0       Obs           2,673,451
25%     .5566371              0       Sum of wgt.   2,673,451

50%     .8941531                      Mean             .80577
                        Largest       Std. dev.      .3799069
75%     1.074272       12.23417
90%     1.223617       12.54532       Variance       .1443293
95%     1.306649        23.8234       Skewness       .0966922
99%     1.485416       40.62791       Kurtosis       54.07609

------------------------------------------------------------------------------------------------------------------------
-> finpat = 1

                      kelly_etal_val_5
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0084298              0
 5%     .0333232              0
10%      .121832              0       Obs              18,155
25%     .4731447              0       Sum of wgt.      18,155

50%     .9923142                      Mean           .8571892
                        Largest       Std. dev.       .472032
75%     1.198638       3.197982
90%     1.362954       3.288105       Variance       .2228142
95%     1.497025       3.693526       Skewness      -.1599198
99%     1.827271       3.978838       Kurtosis       2.572993


. 
. * Table A-4
. 
. ttest weighted if (finpat==1 | academicclass==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1823388    .9983929     .002637     3.56081    .9932245    1.003561
       1 |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
Combined | 1847640    1.001685    .0026186    3.559443    .9965526    1.006817
---------+--------------------------------------------------------------------
    diff |           -.2508154    .0230072               -.2959087   -.2057222
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -10.9016
H0: diff = 0                                     Degrees of freedom =  1.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan if (finpat==1 | academicclass==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 768,453    11.76162    .0335407    29.40227    11.69588    11.82735
       1 |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
Combined | 777,952    12.27257    .0361289     31.8663    12.20176    12.34338
---------+--------------------------------------------------------------------
    diff |           -41.84624    .3255342               -42.48428   -41.20821
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.3e+02
H0: diff = 0                                     Degrees of freedom =   777950

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kelly_etal_val_5 if (finpat==1 | academicclass==1), by(finpat)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 1254635    .8125773    .0003591    .4022062    .8118736    .8132811
       1 |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
Combined | 1272790    .8132137    .0003575    .4033217     .812513    .8139144
---------+--------------------------------------------------------------------
    diff |           -.0446118    .0030146               -.0505204   -.0387032
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -14.7984
H0: diff = 0                                     Degrees of freedom =  1.3e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. 
. median weighted if (finpat==1 | academicclass==1), by(finpat)

Median test

   Greater |
  than the |        finpat
    median |         0          1 |     Total
-----------+----------------------+----------
        no |   912,967     10,980 |   923,947 
       yes |   910,421     13,272 |   923,693 
-----------+----------------------+----------
     Total | 1,823,388     24,252 | 1,847,640 

          Pearson chi2(1) = 220.1316   Pr = 0.000

   Continuity corrected:
          Pearson chi2(1) = 219.9399   Pr = 0.000

. median kogan if (finpat==1 | academicclass==1), by(finpat)

Median test

   Greater |
  than the |        finpat
    median |         0          1 |     Total
-----------+----------------------+----------
        no |   386,510      2,474 |   388,984 
       yes |   381,943      7,025 |   388,968 
-----------+----------------------+----------
     Total |   768,453      9,499 |   777,952 

          Pearson chi2(1) =  2.2e+03   Pr = 0.000

   Continuity corrected:
          Pearson chi2(1) =  2.2e+03   Pr = 0.000

. median kelly_etal_val_5 if (finpat==1 | academicclass==1), by(finpat)

Median test

   Greater |
  than the |        finpat
    median |         0          1 |     Total
-----------+----------------------+----------
        no |   628,335      8,060 |   636,395 
       yes |   626,300     10,095 |   636,395 
-----------+----------------------+----------
     Total | 1,254,635     18,155 | 1,272,790 

          Pearson chi2(1) = 231.4046   Pr = 0.000

   Continuity corrected:
          Pearson chi2(1) = 231.1772   Pr = 0.000

. 
. sum weighted if (finpat==0 & academicclass==1), d

                        weighted_cite
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%            0              0
10%            0              0       Obs           1,823,388
25%            0              0       Sum of wgt.   1,823,388

50%     .1897253                      Mean           .9983929
                        Largest       Std. dev.       3.56081
75%     .8544533       425.5162
90%     2.300221         442.64       Variance       12.67936
95%     4.092049       471.5185       Skewness       26.95698
99%     12.45548       471.5185       Kurtosis       1831.299

. sum kogan if (finpat==0 & academicclass==1), d

                       kogan_etal_val
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0138574       .0002237
 5%     .0406638       .0002718
10%     .1009106       .0002718       Obs             768,453
25%     .9309458       .0002718       Sum of wgt.     768,453

50%     3.779115                      Mean           11.76162
                        Largest       Std. dev.      29.40227
75%     11.14145       2051.981
90%     27.91109       2082.404       Variance       864.4932
95%     46.88818       2145.848       Skewness       12.66773
99%     125.8027       2212.666       Kurtosis       408.8438

. sum kelly_etal_val_5 if (finpat==0 & academicclass==1), d

                      kelly_etal_val_5
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0020039              0
 5%     .0984245              0
10%     .1333541              0       Obs           1,254,635
25%     .5027482              0       Sum of wgt.   1,254,635

50%     .9036534                      Mean           .8125773
                        Largest       Std. dev.      .4022062
75%      1.10575       12.23417
90%      1.26053       12.54532       Variance       .1617698
95%     1.342564        23.8234       Skewness       .6182831
99%     1.532757       40.62791       Kurtosis       89.45583

. 
. * Last piece for Table 1--Annoyingly need to do by hand
. 
. astile weighttile=weighted,nq(100)

. bys weighttile: sum weighted

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |  1,440,443           0           0          0          0

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 38

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |        694    .0126191    .0019778    .004717   .0155553

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 39

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,946    .0501326    .0125582    .015688   .0667604

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 40

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,912    .0777318    .0058384   .0667727   .0876133

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 41

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,918    .0974434    .0053614   .0876174   .1064426

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 42

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     38,301    .1164258    .0054963   .1064785   .1255783

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 43

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,567    .1335028    .0041054   .1255814   .1406454

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 44

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,906    .1488326    .0048773   .1406564   .1575342

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 45

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,926    .1651257    .0045702   .1575419   .1729858

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 46

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,939    .1806964    .0041928   .1729894   .1879815

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 47

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,971    .1962881    .0052327   .1879864   .2055924

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 48

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     38,029    .2152409    .0056547   .2056013   .2243709

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 49

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,761    .2326121    .0044409   .2243714   .2404054

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 50

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,923    .2498304    .0054989   .2404068   .2588832

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 51

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,921    .2674954    .0048897   .2588917   .2766571

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 52

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,984    .2855982    .0051715   .2766724   .2946687

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 53

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     38,079    .3031988    .0052515   .2946708      .3125

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 54

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,761    .3224589    .0054957   .3125225   .3320647

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 55

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,878     .341239    .0055852   .3320734   .3513514

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 56

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,929    .3618094    .0061195   .3513514   .3726708

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 57

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,915    .3830247    .0065183   .3726708   .3954038

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 58

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,955    .4062401    .0061998   .3954082   .4170719

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 59

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     38,229    .4284209    .0067484   .4170732   .4408353

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 60

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,796    .4530096    .0071542   .4408369   .4647455

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 61

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,732    .4769216    .0070831   .4647569   .4895787

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 62

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,975     .501658    .0067851   .4895893   .5131745

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 63

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,864    .5264107    .0071981   .5131767   .5383615

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 64

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,922    .5524698    .0084351   .5383747   .5666335

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 65

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,932    .5811134    .0086613   .5666401   .5961325

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 66

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     38,080    .6109125    .0090151   .5961538   .6260103

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 67

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,767    .6419709     .008686   .6260163   .6577109

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 68

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,920    .6732299    .0089288   .6577181   .6893617

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 69

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,934    .7056141    .0091034   .6893751   .7215877

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 70

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,937     .739926    .0108804   .7215953   .7599283

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 71

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,903    .7783403     .011146   .7599309   .7985707

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 72

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,936    .8193852    .0123569    .798574   .8419722

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 73

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,917    .8622799    .0118386   .8419811   .8839479

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 74

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,922    .9041426    .0121946    .883959   .9262166

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 75

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,936    .9490402     .013224   .9262295   .9722222

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 76

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,921    .9958047     .012607   .9722314   1.018182

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 77

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,916    1.042779    .0153631   1.018229   1.069519

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 78

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,938     1.09872    .0171024   1.069519   1.126733

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 79

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,909    1.158533    .0187753   1.126735    1.19084

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 80

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,966    1.221761    .0185473   1.190865   1.253832

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 81

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,885    1.286439    .0189337   1.253833   1.321492

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 82

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,928     1.35869    .0220694   1.321534   1.397436

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 83

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,956    1.438843      .02398   1.397436   1.481481

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 84

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,890    1.525248    .0260559   1.481481   1.572379

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 85

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,941    1.619305    .0272157   1.572394   1.668153

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 86

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,951     1.72389    .0319469   1.668186    1.78125

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 87

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,881    1.840335    .0362047   1.781285   1.905367

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 88

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,937     1.97348    .0397832   1.905373   2.040816

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 89

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     38,179    2.117731    .0451073   2.040853        2.2

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 90

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,657     2.28805    .0519929    2.20005   2.382893

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 91

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,933    2.483949    .0606744   2.382918   2.587298

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 92

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,924    2.715044    .0744291   2.587307   2.843868

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 93

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,916     2.98319    .0818445   2.843895   3.133483

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 94

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,925    3.320847    .1136194   3.133549    3.52714

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 95

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,925    3.764421    .1433249   3.527141   4.017294

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 96

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,928    4.320566    .1849063   4.017353   4.660378

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 97

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,980    5.126025    .2908585   4.660405   5.666667

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 98

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,865    6.423557    .4773619   5.666667   7.339461

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 99

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,933    8.907984    1.056894   7.339635   11.11111

------------------------------------------------------------------------------------------------------------------------
-> weighttile = 100

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |     37,916    21.53282    18.25977   11.11147   471.5185

------------------------------------------------------------------------------------------------------------------------
-> weighttile = .

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weighted_c~e |          0


. astile kogantile=kogan,nq(100)

. bys kogantile: sum kogan_etal_val

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,258    .0080663     .004612   .0002206   .0138215

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 2

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,262    .0165304    .0015742   .0138487   .0192516

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 3

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,278    .0228329    .0022562   .0192544   .0269858

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 4

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,233    .0307629    .0021946   .0269897   .0344299

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 5

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,272    .0379522     .002173   .0344479   .0416533

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 6

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,244    .0458434    .0026289   .0416547   .0507434

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 7

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,263    .0559349    .0028854   .0507455   .0609986

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 8

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,260    .0664428    .0031831   .0610035   .0721348

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 9

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,253    .0790415     .004031   .0721709   .0864138

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 10

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,266    .0935569    .0046129   .0864227   .1019344

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 11

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,258    .1129685    .0060715   .1019717   .1231021

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 12

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,272    .1344315    .0066373   .1231632   .1463614

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 13

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,236    .1583462    .0072566   .1463933   .1709355

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 14

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    .1813978    .0064828   .1709462   .1940563

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 15

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,249    .2053962    .0067449   .1940612   .2173698

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 16

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,250    .2324881    .0086197   .2174139   .2478302

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 17

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,267    .2649807    .0098385   .2478492    .282521

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 18

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,269    .3022161    .0121514   .2826354   .3242707

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 19

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,231    .3468177    .0130736   .3242868   .3694902

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 20

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,267     .394794    .0157473   .3695047   .4223276

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 21

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,248    .4522853    .0172951   .4223294   .4825594

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 22

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,275    .5166302    .0211327   .4825711   .5540771

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 23

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,268    .5968901    .0243651   .5541083   .6393893

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 24

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,229    .6832688    .0253691   .6393971   .7277846

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 25

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    .7779302    .0279904   .7277921   .8280409

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 26

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,262    .8781572    .0290649   .8280436    .931236

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 27

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,247    .9718602    .0260011    .931263   1.018631

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 28

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,258    1.069822    .0296384   1.018695   1.120038

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 29

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,261    1.170949    .0296992   1.120054   1.222494

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 30

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,251     1.26456    .0244517   1.222592   1.309854

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 31

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    1.354048    .0263249   1.309855   1.403909

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 32

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,358    1.449037    .0265697    1.40391   1.499961

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 33

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,167    1.549262     .030297   1.499992   1.603243

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 34

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,259    1.652671    .0288328   1.603245   1.700431

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 35

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,243    1.750953      .03087   1.700498   1.804694

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 36

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,295    1.854044    .0308417   1.804788    1.90536

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 37

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,221    1.960191    .0327454   1.905518   2.019877

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 38

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,276    2.078688    .0368079   2.019912   2.143794

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 39

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,235    2.211157    .0397342   2.143882   2.281609

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 40

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,262    2.353687    .0426876   2.281656   2.427875

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 41

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,251    2.500368     .044755   2.427894   2.582178

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 42

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,280    2.648907    .0370386   2.582223    2.71657

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 43

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,235    2.789165    .0393707   2.716637    2.86134

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 44

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,255    2.942528    .0471641   2.861358   3.023809

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 45

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,272    3.104848     .047508    3.02386   3.187141

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 46

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,264    3.267161     .046635   3.187171    3.34669

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 47

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,234    3.428993    .0488817   3.347049   3.513154

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 48

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,262    3.606071    .0529464   3.513186   3.698846

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 49

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,251    3.785103    .0516493   3.699107   3.878029

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 50

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,334    3.975955    .0582471   3.878191   4.076221

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 51

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,180    4.162544    .0497671   4.076361    4.24964

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 52

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,273    4.357618    .0636662   4.249731   4.468004

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 53

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,270    4.574809     .057981   4.468044   4.670874

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 54

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,228    4.772147    .0591384   4.670951   4.876902

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 55

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,282    4.988909    .0649407   4.877032   5.096159

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 56

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,231    5.199424    .0607607   5.096191   5.304766

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 57

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,260    5.422412    .0677945   5.304892   5.540452

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 58

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,278     5.66166    .0694531   5.540493   5.776483

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 59

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,232    5.898486    .0720304   5.776512   6.022762

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 60

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,259    6.143237    .0690423   6.022802   6.266041

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 61

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,256    6.393977     .074843   6.266182   6.521087

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 62

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,255    6.656147    .0777392   6.521173   6.791165

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 63

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,264    6.938878    .0843468   6.791268   7.079657

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 64

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,252    7.219793    .0843161   7.079798   7.364207

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 65

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,262    7.522935    .0924359   7.364449   7.680333

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 66

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,281    7.831329    .0912247   7.680478   7.994523

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 67

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,245    8.151854    .0895135   7.994692    8.30544

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 68

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,261    8.486466    .0991771   8.305614   8.652238

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 69

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,239    8.829239     .101199   8.652266   9.001329

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 70

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,250    9.185869    .1082875   9.001385    9.37061

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 71

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,273    9.568138    .1124033   9.370811   9.761934

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 72

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,239    9.959184    .1168812   9.762202   10.16281

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 73

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,264    10.38662    .1248668   10.16282   10.59579

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 74

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,261    10.81721    .1328956    10.5958   11.05725

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 75

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,247    11.31627    .1454824    11.0575   11.55875

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 76

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,255    11.83307    .1520224   11.55884   12.10185

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 77

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    12.37705     .166399     12.102   12.67897

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 78

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,279    12.98106    .1782356   12.67931   13.29575

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 79

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,238    13.63634    .1917384    13.2958   13.96893

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 80

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,255    14.34557    .2188365   13.96905   14.71927

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 81

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,259    15.09493    .2233633   14.71949   15.49826

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 82

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,261    15.90086    .2250391   15.49884   16.30053

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 83

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,250    16.80405    .2956936   16.30121   17.30579

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 84

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,263    17.84271    .3278095   17.30649   18.42268

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 85

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,248    18.97295     .325046   18.42301   19.55811

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 86

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,289    20.19065    .3876642    19.5584   20.85597

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 87

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,233    21.58762    .4172494   20.85604   22.29031

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 88

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,248    23.12276    .4921958    22.2912   23.96652

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 89

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    24.90117    .5529464   23.96733   25.87738

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 90

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,259    26.95771    .6312055   25.87753   28.06367

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 91

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,263    29.23311    .7083012    28.0639   30.55886

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 92

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,248    31.99318    .8622642   30.55948   33.49389

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 93

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    35.16419    .9910636   33.49532   36.95211

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 94

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    39.10132    1.289902   36.95234   41.42178

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 95

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,262    44.22583    1.690852   41.42209   47.25698

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 96

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,272    50.75255    2.087053   47.25938   54.51482

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 97

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,235    60.22484    3.463101   54.51502    66.4762

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 98

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    75.41277    5.636656    66.4776    85.8991

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 99

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,257    103.8052    12.25483   85.90234   128.2354

------------------------------------------------------------------------------------------------------------------------
-> kogantile = 100

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |     13,256    232.7182    172.1893   128.2557   5199.875

------------------------------------------------------------------------------------------------------------------------
-> kogantile = .

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kogan_etal~l |          0


. astile kellytile=kelly_etal_val_5,nq(100)

. bys kellytile: sum kelly_etal_val_5

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .0027619    .0053011          0   .0185342

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 2

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .0230725    .0019596   .0185344   .0259436

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 3

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .0278937    .0010536   .0259437   .0296856

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 4

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .0323138    .0019678   .0296857   .0374096

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 5

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .0858941    .0178042   .0374099   .1010476

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 6

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .1063348    .0027939   .1010482   .1107687

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 7

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .1141538    .0018497   .1107687   .1172229

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 8

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .1200229    .0016122    .117223   .1228834

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 9

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .1265043    .0023276   .1228835   .1310081

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 10

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .1445626    .0148704   .1310084   .1949665

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 11

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .2202084    .0099428   .1949677   .2335944

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 12

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     .242571    .0048211   .2335947   .2503293

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 13

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .2563402    .0033376   .2503294   .2619061

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 14

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .2671288    .0030042   .2619065   .2723518

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 15

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .2781558    .0035251   .2723531   .2846045

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 16

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916      .29286    .0051824   .2846045   .3027514

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 17

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .3240254    .0172047   .3027515   .3613679

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 18

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .3827334    .0098997   .3613699   .3972029

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 19

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .4067979    .0052258   .3972031   .4156196

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 20

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .4241096    .0048597   .4156198   .4323925

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 21

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .4403346    .0045528   .4323925   .4481699

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 22

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .4562792     .004744   .4481727   .4647025

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 23

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .4745354    .0059898   .4647042   .4855979

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 24

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .5005844    .0093282    .485598   .5178201

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 25

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .5374251    .0110346   .5178201   .5554612

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 26

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .5693958     .007693   .5554613   .5821922

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 27

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .5932317    .0062119   .5821923   .6037256

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 28

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .6135018    .0056117    .603726   .6232265

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 29

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     .633075    .0056515   .6232282   .6429476

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 30

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     .652947     .005747   .6429478   .6628289

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 31

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .6725413    .0055613   .6628293   .6820976

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 32

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .6918742    .0056402   .6820977   .7016295

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 33

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .7113229    .0055883   .7016303     .72094

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 34

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .7302071    .0052919   .7209406    .739282

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 35

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .7476096    .0046963    .739282   .7555863

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 36

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .7629249    .0041331   .7555863   .7699269

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 37

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .7762634    .0035881   .7699271   .7823338

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 38

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .7880958    .0032532   .7823343   .7936485

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 39

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .7988353    .0029977   .7936487   .8039914

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 40

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .8089686    .0028607   .8039916   .8138771

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 41

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    .8186154    .0027203   .8138772   .8233137

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 42

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .8278363    .0025845   .8233142   .8322699

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 43

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .8364907    .0024321   .8322704   .8407409

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 44

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .8448509    .0023549   .8407415   .8489102

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 45

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .8528934    .0022863   .8489102    .856821

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 46

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .8607519    .0022488   .8568211   .8645986

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 47

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916      .86844     .002188    .864599   .8722014

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 48

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917     .875976    .0021744   .8722019   .8797296

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 49

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    .8834596    .0021493   .8797303    .887185

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 50

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .8908206    .0020926   .8871852   .8944169

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 51

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .8979938    .0020646   .8944176   .9015544

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 52

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .9050664    .0020163   .9015545   .9085537

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 53

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    .9120546    .0020145   .9085538   .9155445

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 54

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9190231    .0020018   .9155446   .9224855

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 55

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9260167    .0020258   .9224858   .9295044

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 56

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9329251    .0019923   .9295054   .9363915

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 57

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9398382    .0019954   .9363915   .9433069

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 58

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9467919    .0020113   .9433072   .9502972

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 59

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9537865    .0020203   .9502978   .9572762

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 60

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9607507    .0020122   .9572763   .9642126

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 61

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9677488    .0020464   .9642132   .9712797

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 62

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9748647    .0020729   .9712801   .9784616

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 63

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    .9820485    .0020817   .9784617   .9856493

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 64

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    .9892494    .0020506   .9856494   .9927992

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 65

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    .9963807    .0020692   .9927993   .9999585

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 66

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    1.003587    .0020865    .999959   1.007153

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 67

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     1.01079    .0020967   1.007153   1.014424

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 68

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.018073    .0021203   1.014424   1.021764

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 69

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,918    1.025454    .0021273   1.021764   1.029136

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 70

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,914    1.032822    .0021476   1.029136   1.036559

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 71

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.040247    .0021424   1.036559   1.043982

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 72

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.047827    .0022077   1.043982   1.051655

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 73

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.055512    .0022395   1.051655   1.059386

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 74

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.063298    .0022725   1.059386   1.067207

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 75

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    1.071165    .0022959   1.067208   1.075176

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 76

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    1.079266    .0023662   1.075176   1.083345

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 77

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     1.08747     .002394   1.083345   1.091653

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 78

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    1.095924    .0024542   1.091653     1.1002

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 79

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    1.104492     .002486     1.1002   1.108844

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 80

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,918    1.113246    .0025686   1.108845    1.11771

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 81

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,914    1.122216    .0026072    1.11771    1.12679

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 82

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    1.131418    .0026932   1.126791   1.136106

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 83

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    1.140866    .0027636   1.136106   1.145684

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 84

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,918    1.150686    .0028951   1.145684   1.155693

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 85

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915    1.160859    .0029946   1.155693   1.166039

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 86

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.171296    .0030662    1.16604   1.176676

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 87

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,917    1.182177    .0031868   1.176677   1.187736

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 88

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,915     1.19353    .0033734   1.187737   1.199435

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 89

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.205529    .0035523   1.199436   1.211681

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 90

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.218121    .0037496   1.211681   1.224648

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 91

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.231455    .0039735   1.224648   1.238419

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 92

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.245827     .004329   1.238419   1.253341

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 93

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.261358    .0046897   1.253342   1.269557

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 94

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     1.27833    .0051857   1.269558     1.2875

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 95

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.297516     .005927   1.287503    1.30803

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 96

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.319721    .0070005   1.308031   1.332405

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 97

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.347422    .0090734   1.332405   1.363821

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 98

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916     1.38412    .0125089   1.363823   1.407294

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 99

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.442076     .023069     1.4073   1.489028

------------------------------------------------------------------------------------------------------------------------
-> kellytile = 100

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |     26,916    1.674944    .4038038    1.48903   40.62791

------------------------------------------------------------------------------------------------------------------------
-> kellytile = .

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
kelly_etal~5 |          0


. 
. * Now just looking at finance patents
. * Merging in the data
. 
. use financial_patent_data_v3, clear

. merge m:1 patent_id using BS_FintechPatents

    Result                      Number of obs
    -----------------------------------------
    Not matched                         1,058
        from master                     1,058  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            23,197  (_merge==3)
    -----------------------------------------

. drop _merge

. merge m:1 patent_id using FS_FintechPatents

    Result                      Number of obs
    -----------------------------------------
    Not matched                         1,058
        from master                     1,058  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            23,197  (_merge==3)
    -----------------------------------------

. drop _merge

. gen grant_year=year(grant_date)

. gen kelly_yuan=fs/bs if grant_year<=2015
(6,639 missing values generated)

. drop fs bs grant_year

. ren patent_id patent

. merge 1:1 patent using cite

    Result                      Number of obs
    -----------------------------------------
    Not matched                     1,074,957
        from master                    15,594  (_merge==1)
        from using                  1,059,363  (_merge==2)

    Matched                             8,661  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(1,059,363 observations deleted)

. drop _merge

. replace cite=0 if cite==.
(15,594 real changes made)

. merge 1:1 patent using citetopq

    Result                      Number of obs
    -----------------------------------------
    Not matched                       563,786
        from master                    21,407  (_merge==1)
        from using                    542,379  (_merge==2)

    Matched                             2,848  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(542,379 observations deleted)

. drop _merge

. replace citetopq=0 if citetopq==.
(21,407 real changes made)

. merge 1:1 patent using citeeconbus

    Result                      Number of obs
    -----------------------------------------
    Not matched                        62,682
        from master                    20,200  (_merge==1)
        from using                     42,482  (_merge==2)

    Matched                             4,055  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(42,482 observations deleted)

. drop _merge

. replace citeeconbus=0 if citeeconbus==.
(20,200 real changes made)

. merge 1:1 patent using citeit

    Result                      Number of obs
    -----------------------------------------
    Not matched                       610,508
        from master                    18,708  (_merge==1)
        from using                    591,800  (_merge==2)

    Matched                             5,547  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(591,800 observations deleted)

. drop _merge

. replace citeit=0 if citeit==.
(18,708 real changes made)

. merge 1:1 patent using citeeconbustopq

    Result                      Number of obs
    -----------------------------------------
    Not matched                        32,123
        from master                    23,269  (_merge==1)
        from using                      8,854  (_merge==2)

    Matched                               986  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(8,854 observations deleted)

. drop _merge

. replace citeeconbustopq=0 if citeeconbustopq==.
(23,269 real changes made)

. merge 1:1 patent using citetop3

    Result                      Number of obs
    -----------------------------------------
    Not matched                        23,926
        from master                    23,745  (_merge==1)
        from using                        181  (_merge==2)

    Matched                               510  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(181 observations deleted)

. drop _merge

. replace citetop3=0 if citetop3==.
(23,745 real changes made)

. merge 1:1 patent using citepractop3

    Result                      Number of obs
    -----------------------------------------
    Not matched                        24,062
        from master                    23,820  (_merge==1)
        from using                        242  (_merge==2)

    Matched                               435  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(242 observations deleted)

. drop _merge

. replace citetopprac3=0 if citetopprac3==.
(23,820 real changes made)

. merge 1:1 patent using citeage

    Result                      Number of obs
    -----------------------------------------
    Not matched                     1,074,957
        from master                    15,594  (_merge==1)
        from using                  1,059,363  (_merge==2)

    Matched                             8,661  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(1,059,363 observations deleted)

. drop _merge

. 
. * Consolidating in the categories
. 
. * 7 industries
. 
. gen bank=(primary_industry=="Diversified Banks" | primary_industry=="Regional Banks" | primary_industry=="Thrifts and 
> Mortgage Finance")

. gen capmkt=(primary_industry=="Asset Management and Custody Banks" | primary_industry=="Diversified Capital Markets" |
>  primary_industry=="Diversified REITs" | primary_industry=="Financial Exchanges and Data" | primary_industry=="Investm
> ent Banking and Brokerage" | primary_industry=="Specialized REITs") 

. gen consfin=(primary_industry=="Consumer Finance" | primary_industry=="Specialized Finance")

. gen insur=(primary_industry=="Life and Health Insurance" | primary_industry=="Multi-line Insurance" | primary_industry
> =="Property and Casualty Insurance" | primary_industry=="Reinsurance")

. gen pay=(primary_industry=="Data Processing and Outsourced Services")

. gen it=(primary_industry=="Application Software" | primary_industry=="Communications Equipment" | primary_industry=="C
> onsumer Electronics" | primary_industry=="Electrical Components and Equipment" | primary_industry=="Electronic Compone
> nts")

. replace it=1 if (primary_industry=="IT Consulting and Other Services" | primary_industry=="Electronic Equipment and In
> struments" | primary_industry=="Electronic Manufacturing Services" | primary_industry=="Integrated Telecommunication S
> ervices" | primary_industry=="Interactive Media and Services")
(1,967 real changes made)

. replace it=1 if (primary_industry=="Internet Services and Infrastructure" | primary_industry=="Internet and Direct Mar
> keting Retail" | primary_industry=="Semiconductor Equipment" | primary_industry=="Semiconductors" | primary_industry==
> "Specialized Consumer Services" | primary_industry=="Systems Software")
(1,862 real changes made)

. replace it=1 if (primary_industry=="Technology Distributors" | primary_industry=="Technology Hardware, Storage and Per
> ipherals" | primary_industry=="Wireless Telecommunication Services")
(1,883 real changes made)

. gen otherind=(bank==0 & capmkt==0 & consfin==0 & insur==0 & pay==0 & it==0)

. gen industrytype=1 if bank==1
(22,654 missing values generated)

. replace industrytype=2 if capmkt==1
(1,618 real changes made)

. replace industrytype=3 if consfin==1
(715 real changes made)

. replace industrytype=4 if insur==1
(1,098 real changes made)

. replace industrytype=5 if pay==1
(2,390 real changes made)

. replace industrytype=6 if it==1
(9,057 real changes made)

. replace industrytype=7 if industrytype==.
(7,776 real changes made)

. label define industrytype1 1 "bank" 2 "capmkt" 3 "consfin" 4 "insur" 5 "pay" 6 "it" 7 "otherind" 

. label values industrytype industrytype1

. 
. * 3 applications
. 
. gen payapp=(payments>=0.5)

. gen bankapp=(commercial_banking+investment_banking+retail_banking>=0.5)

. gen otherapp=(bankapp~=1 & payapp~=1)

. gen apptype=1 if payapp==1
(13,601 missing values generated)

. replace apptype=2 if bankapp==1
(5,486 real changes made)

. replace apptype=3 if apptype==.
(9,924 real changes made)

. label define apptype1 1 "payments" 2 "banking" 3 "otherapp"

. label values apptype apptype1

. 
. * 2 geographies
. 
. gen us=(inventor_1_country=="US")

. gen othernation=(us==0)

. gen nationtype=1 if us==1
(5,103 missing values generated)

. replace nationtype=2 if nationtype==.
(5,103 real changes made)

. label define nationtype1 1 "us" 2 "not us"

. label values nationtype nationtype1 

. 
. * Academic
. 
. rename patent patent_id

. merge 1:1 patent_id using university_patent

    Result                      Number of obs
    -----------------------------------------
    Not matched                       112,953
        from master                    24,193  (_merge==1)
        from using                     88,760  (_merge==2)

    Matched                                62  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(88,760 observations deleted)

. gen academic=(_merge==3)

. drop _merge

. gen noncorporate=((assignee_type>=4 & assignee_type<=7) | assignee_type==.)

. replace revenue=revenue/1000000
(13,308 real changes made)

. 
. * Setting up
. 
. gen indsimpletype=1 if (industrytype==1)
(22,654 missing values generated)

. replace indsimpletype=2 if (industrytype>=2 & industrytype<=4)
(3,431 real changes made)

. replace indsimpletype=5 if (industrytype==5)
(2,390 real changes made)

. replace indsimpletype=7 if (industrytype==6 | industrytype==7)
(16,833 real changes made)

. 
. gen appyr="early" if (app_year<2005)
(18,938 missing values generated)

. replace appyr="mid" if (app_year>=2005 & app_year<2010)
(7,564 real changes made)

. replace appyr=" late" if (app_year>=2010 & app_year<2015)
(8,881 real changes made)

. replace appyr="latest" if (app_year>=2015)
variable appyr was str5 now str6
(2,493 real changes made)

. 
. * Table A-13
. 
. gen anycite=(cite~=0)

. gen anycitetopq=(citetopq~=0)

. gen anyciteeconbus=(citeeconbus~=0)

. gen anyciteit=(citeit~=0)

. gen anyciteeconbustopq=(citeeconbustopq~=0)

. gen anycitetop3=(citetop3~=0)

. gen anycitetopprac3=(citetopprac3~=0)

. ttest weighted_cite, by(anycite)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  15,591    1.114291    .0270489    3.377427    1.061272     1.16731
       1 |   8,661    1.492079    .0381891    3.554045    1.417219    1.566938
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |           -.3777877    .0461217               -.4681892   -.2873863
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -8.1911
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest weighted_cite, by(anycitetopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  21,404    1.164646      .02211    3.234719    1.121309    1.207983
       1 |   2,848    1.884732    .0879822    4.695315    1.712217    2.057247
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |           -.7200858    .0685842               -.8545152   -.5856565
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -10.4993
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest weighted_cite, by(anyciteeconbus)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  20,197    1.223335    .0241047    3.425673    1.176088    1.270582
       1 |   4,055    1.378077    .0556613     3.54445    1.268951    1.487204
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |           -.1547425    .0592962               -.2709667   -.0385183
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -2.6097
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0045         Pr(|T| > |t|) = 0.0091          Pr(T > t) = 0.9955

. ttest weighted_cite, by(anyciteit)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  18,705    1.100772    .0237545    3.248815    1.054211    1.147333
       1 |   5,547    1.749751    .0537257    4.001389    1.644427    1.855074
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |           -.6489791    .0525238               -.7519289   -.5460293
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -12.3559
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest weighted_cite, by(anyciteeconbustopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  23,266    1.237535    .0224366    3.422302    1.193558    1.281512
       1 |     986     1.52465     .126149    3.961158    1.277099    1.772202
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |           -.2871151    .1120388               -.5067181   -.0675121
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -2.5626
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0052         Pr(|T| > |t|) = 0.0104          Pr(T > t) = 0.9948

. ttest weighted_cite, by(anycitetop3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  23,742    1.248116    .0224554    3.460029    1.204102     1.29213
       1 |     510    1.300058    .1208725    2.729685    1.062588    1.537529
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |           -.0519422    .1542346               -.3542516    .2503671
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -0.3368
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.3681         Pr(|T| > |t|) = 0.7363          Pr(T > t) = 0.6319

. ttest weighted_cite, by(anycitetopprac3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  23,817    1.257818    .0225023    3.472733    1.213712    1.301924
       1 |     435    .7778375    .0608993    1.270156    .6581432    .8975317
---------+--------------------------------------------------------------------
Combined |  24,252    1.249208    .0221294    3.446227    1.205833    1.292583
---------+--------------------------------------------------------------------
    diff |            .4799801     .166711                .1532162    .8067439
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   2.8791
H0: diff = 0                                     Degrees of freedom =    24250

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9980         Pr(|T| > |t|) = 0.0040          Pr(T > t) = 0.0020

. ttest kogan_etal_val, by(anycite)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   6,154    50.18368    1.211641    95.05013    47.80844    52.55892
       1 |   3,345    59.90753      2.1856    126.4063    55.62228    64.19278
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |           -9.723854    2.301577               -14.23544   -5.212272
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -4.2249
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan_etal_val, by(anycitetopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   8,457      51.701    1.101002    101.2503    49.54277    53.85924
       1 |   1,042    69.08411    4.529909    146.2256    60.19532    77.97291
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |           -17.38311    3.516494               -24.27619   -10.49003
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -4.9433
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan_etal_val, by(anyciteeconbus)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   8,073    48.00254    1.062916    95.50285    45.91896    50.08613
       1 |   1,426    85.34116     4.08528    154.2701    77.32735    93.35497
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |           -37.33861    3.056662               -43.33032    -31.3469
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -12.2155
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan_etal_val, by(anyciteit)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   7,220    54.16958    1.217364    103.4401    51.78319    56.55597
       1 |   2,279    51.82828    2.481735    118.4752    46.96158    56.69498
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |            2.341303     2.57662               -2.709423    7.392029
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   0.9087
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.8182         Pr(|T| > |t|) = 0.3635          Pr(T > t) = 0.1818

. ttest kogan_etal_val, by(anyciteeconbustopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   9,208    52.25026    1.066501    102.3396    50.15968    54.34084
       1 |     291    96.56582     12.0453    205.4774    72.85853    120.2731
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |           -44.31556     6.36908               -56.80032    -31.8308
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -6.9579
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan_etal_val, by(anycitetop3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   9,390    52.09158    1.052933    102.0313     50.0276    54.15556
       1 |     109    184.2302     28.5599    298.1741    127.6195    240.8409
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |           -132.1386    10.24215               -152.2154   -112.0618
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -12.9015
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kogan_etal_val, by(anycitetopprac3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |   9,360    53.36926     1.10901    107.2935    51.19536    55.54316
       1 |     139    69.67463    8.695309    102.5162    52.48137     86.8679
---------+--------------------------------------------------------------------
Combined |   9,499    53.60786    1.100295    107.2379    51.45104    55.76467
---------+--------------------------------------------------------------------
    diff |           -16.30537    9.162041               -34.26493    1.654187
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -1.7797
H0: diff = 0                                     Degrees of freedom =     9497

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0376         Pr(|T| > |t|) = 0.0752          Pr(T > t) = 0.9624

. ttest kelly_etal_val_5, by(anycite)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  11,206    .8342467    .0043718    .4627947    .8256772    .8428163
       1 |   6,949    .8941863    .0058098     .484308    .8827973    .9055753
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |           -.0599396    .0071939               -.0740404   -.0458388
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -8.3320
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kelly_etal_val_5, by(anycitetopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  15,943    .8551899    .0037178    .4694295    .8479026    .8624772
       1 |   2,212    .8715989    .0104238    .4902495    .8511575    .8920403
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |            -.016409    .0107097                -.037401    .0045829
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -1.5322
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0627         Pr(|T| > |t|) = 0.1255          Pr(T > t) = 0.9373

. ttest kelly_etal_val_5, by(anyciteeconbus)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  14,651    .8475606     .003844    .4652873    .8400258    .8550954
       1 |   3,504    .8974484    .0084011    .4973006    .8809769      .91392
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |           -.0498879    .0088693               -.0672725   -.0325033
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -5.6248
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kelly_etal_val_5, by(anyciteit)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  13,986    .8453223    .0039753     .470127    .8375302    .8531144
       1 |   4,169    .8969996    .0073763    .4762689    .8825382     .911461
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |           -.0516772    .0083207               -.0679865    -.035368
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -6.2107
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest kelly_etal_val_5, by(anyciteeconbustopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  17,334    .8547283    .0035676    .4697113    .8477354    .8617213
       1 |     821    .9091458    .0180151    .5161882    .8737847    .9445069
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |           -.0544175    .0168553               -.0874554   -.0213795
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.2285
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0006         Pr(|T| > |t|) = 0.0012          Pr(T > t) = 0.9994

. ttest kelly_etal_val_5, by(anycitetop3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  17,710    .8553565    .0035332    .4701928    .8484311    .8622819
       1 |     445    .9301241    .0253943    .5356937    .8802161    .9800321
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |           -.0747675    .0226497                -.119163    -.030372
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.3010
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0005         Pr(|T| > |t|) = 0.0010          Pr(T > t) = 0.9995

. ttest kelly_etal_val_5, by(anycitetopprac3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  17,747    .8552554    .0035395    .4715289    .8483176    .8621933
       1 |     408    .9413019    .0240915    .4866242    .8939426    .9886612
---------+--------------------------------------------------------------------
Combined |  18,155    .8571892    .0035033     .472032    .8503224    .8640559
---------+--------------------------------------------------------------------
    diff |           -.0860465    .0236282               -.1323599    -.039733
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.6417
H0: diff = 0                                     Degrees of freedom =    18153

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0001         Pr(|T| > |t|) = 0.0003          Pr(T > t) = 0.9999

. ttest kelly_yuan, by(anycite)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  10,962    1.591789    .0087698    .9181896    1.574599     1.60898
       1 |   6,654    1.613957    .0113843    .9286412     1.59164    1.636274
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |           -.0221672    .0143308               -.0502569    .0059225
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -1.5468
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0610         Pr(|T| > |t|) = 0.1219          Pr(T > t) = 0.9390

. ttest kelly_yuan, by(anycitetopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  15,456     1.60773    .0074685    .9285002    1.593091    1.622369
       1 |   2,160    1.546011    .0188052    .8739861    1.509133    1.582889
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |            .0617195     .021179                .0202066    .1032324
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   2.9142
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9982         Pr(|T| > |t|) = 0.0036          Pr(T > t) = 0.0018

. ttest kelly_yuan, by(anyciteeconbus)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  14,290    1.604807    .0077602    .9276572    1.589596    1.620018
       1 |   3,326    1.580207    .0155739    .8981725    1.549671    1.610742
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |            .0246003    .0177535               -.0101983     .059399
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   1.3857
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9171         Pr(|T| > |t|) = 0.1659          Pr(T > t) = 0.0829

. ttest kelly_yuan, by(anyciteit)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  13,587    1.586732    .0078117    .9105544     1.57142    1.602044
       1 |   4,029    1.645453    .0151102    .9591109    1.615828    1.675077
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |           -.0587204    .0165375               -.0911355   -.0263053
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.5507
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0002         Pr(|T| > |t|) = 0.0004          Pr(T > t) = 0.9998

. ttest kelly_yuan, by(anyciteeconbustopq)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  16,827    1.605174    .0071603    .9288327    1.591139    1.619209
       1 |     789     1.49328    .0270402    .7595347    1.440201    1.546359
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |             .111894     .033582                  .04607     .177718
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   3.3320
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9996         Pr(|T| > |t|) = 0.0009          Pr(T > t) = 0.0004

. ttest kelly_yuan, by(anycitetop3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  17,195    1.602579    .0070492    .9243537    1.588762    1.616396
       1 |     421    1.501481    .0401515      .82384    1.422558    1.580404
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |            .1010974    .0454865                .0119394    .1902553
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   2.2226
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9869         Pr(|T| > |t|) = 0.0263          Pr(T > t) = 0.0131

. ttest kelly_yuan, by(anycitetopprac3)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 |  17,227    1.600198    .0070208    .9214909    1.586437     1.61396
       1 |     389     1.59857    .0483572    .9537537    1.503495    1.693645
---------+--------------------------------------------------------------------
Combined |  17,616    1.600163    .0069481    .9221876    1.586544    1.613781
---------+--------------------------------------------------------------------
    diff |            .0016283    .0472831               -.0910512    .0943077
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   0.0344
H0: diff = 0                                     Degrees of freedom =    17614

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.5137         Pr(|T| > |t|) = 0.9725          Pr(T > t) = 0.4863

. drop anycite anycitetopq anyciteeconbus anyciteit anyciteeconbustopq anycitetop3 anycitetopprac3

. 
. * Table 7, Panel A
. 
. gen fintech=(crypto+payments+security)>0

. pwcorr grant_date cite citetopq citeeconbus citeit citeeconbustopq citetop3 citetopprac3 citeage, sig

             | grant_~e     cite citetopq citeec~s   citeit citeec~q citetop3
-------------+---------------------------------------------------------------
  grant_date |   1.0000 
             |
             |
        cite |  -0.0133   1.0000 
             |   0.0385
             |
    citetopq |   0.0071   0.8367   1.0000 
             |   0.2692   0.0000
             |
 citeeconbus |  -0.0307   0.4422   0.4954   1.0000 
             |   0.0000   0.0000   0.0000
             |
      citeit |  -0.0085   0.9446   0.7583   0.1821   1.0000 
             |   0.1862   0.0000   0.0000   0.0000
             |
citeeconbu~q |  -0.0159   0.3223   0.5304   0.7998   0.1195   1.0000 
             |   0.0130   0.0000   0.0000   0.0000   0.0000
             |
    citetop3 |  -0.0273   0.2223   0.3790   0.6777   0.0490   0.8556   1.0000 
             |   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000
             |
citetopprac3 |  -0.0304   0.1443   0.1916   0.5282   0.0080   0.4448   0.4777 
             |   0.0000   0.0000   0.0000   0.0000   0.2128   0.0000   0.0000
             |
     citeage |   0.1775   0.1160   0.0841   0.1199   0.0729   0.0702   0.1058 
             |   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000
             |

             | citet~c3  citeage
-------------+------------------
citetopprac3 |   1.0000 
             |
             |
     citeage |   0.0508   1.0000 
             |   0.0000
             |

. by indsimple, sort: pwcorr grant_date cite citetopq citeeconbus citeit citeeconbustopq citetop3 citetopprac3 citeage, 
> sig

------------------------------------------------------------------------------------------------------------------------
-> indsimpletype = 1

             | grant_~e     cite citetopq citeec~s   citeit citeec~q citetop3
-------------+---------------------------------------------------------------
  grant_date |   1.0000 
             |
             |
        cite |  -0.2345   1.0000 
             |   0.0000
             |
    citetopq |  -0.1196   0.6671   1.0000 
             |   0.0000   0.0000
             |
 citeeconbus |  -0.2856   0.7636   0.4483   1.0000 
             |   0.0000   0.0000   0.0000
             |
      citeit |  -0.1306   0.8814   0.5984   0.4251   1.0000 
             |   0.0000   0.0000   0.0000   0.0000
             |
citeeconbu~q |  -0.1299   0.3306   0.6220   0.4126   0.2435   1.0000 
             |   0.0000   0.0000   0.0000   0.0000   0.0000
             |
    citetop3 |  -0.1525   0.2836   0.4839   0.3730   0.2000   0.8130   1.0000 
             |   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000
             |
citetopprac3 |  -0.0543   0.0686   0.1262   0.1165   0.0425   0.2952   0.2781 
             |   0.0297   0.0060   0.0000   0.0000   0.0891   0.0000   0.0000
             |
     citeage |   0.1692   0.1739   0.1702   0.0379   0.1717   0.0396   0.0979 
             |   0.0000   0.0000   0.0000   0.3525   0.0000   0.3304   0.0160
             |

             | citet~c3  citeage
-------------+------------------
citetopprac3 |   1.0000 
             |
             |
     citeage |  -0.0629   1.0000 
             |   0.1224
             |

------------------------------------------------------------------------------------------------------------------------
-> indsimpletype = 2

             | grant_~e     cite citetopq citeec~s   citeit citeec~q citetop3
-------------+---------------------------------------------------------------
  grant_date |   1.0000 
             |
             |
        cite |   0.0051   1.0000 
             |   0.7650
             |
    citetopq |  -0.0137   0.7667   1.0000 
             |   0.4238   0.0000
             |
 citeeconbus |  -0.0752   0.7855   0.7510   1.0000 
             |   0.0000   0.0000   0.0000
             |
      citeit |   0.0597   0.7282   0.4026   0.1859   1.0000 
             |   0.0005   0.0000   0.0000   0.0000
             |
citeeconbu~q |  -0.0564   0.5647   0.8591   0.8102   0.0369   1.0000 
             |   0.0009   0.0000   0.0000   0.0000   0.0309
             |
    citetop3 |  -0.0672   0.5295   0.8100   0.7680   0.0307   0.9269   1.0000 
             |   0.0001   0.0000   0.0000   0.0000   0.0722   0.0000
             |
citetopprac3 |  -0.0667   0.4999   0.4612   0.7232   0.0194   0.5101   0.5393 
             |   0.0001   0.0000   0.0000   0.0000   0.2559   0.0000   0.0000
             |
     citeage |   0.1601   0.0832   0.0135   0.0835   0.0466   0.0233   0.0541 
             |   0.0000   0.0009   0.5929   0.0009   0.0644   0.3559   0.0319
             |

             | citet~c3  citeage
-------------+------------------
citetopprac3 |   1.0000 
             |
             |
     citeage |   0.0376   1.0000 
             |   0.1360
             |

------------------------------------------------------------------------------------------------------------------------
-> indsimpletype = 5

             | grant_~e     cite citetopq citeec~s   citeit citeec~q citetop3
-------------+---------------------------------------------------------------
  grant_date |   1.0000 
             |
             |
        cite |  -0.0877   1.0000 
             |   0.0000
             |
    citetopq |  -0.0929   0.6409   1.0000 
             |   0.0000   0.0000
             |
 citeeconbus |  -0.0092   0.5051   0.4417   1.0000 
             |   0.6523   0.0000   0.0000
             |
      citeit |  -0.0830   0.9055   0.4908   0.1583   1.0000 
             |   0.0000   0.0000   0.0000   0.0000
             |
citeeconbu~q |   0.0322   0.1698   0.5305   0.3496   0.0533   1.0000 
             |   0.1160   0.0000   0.0000   0.0000   0.0091
             |
    citetop3 |  -0.0253   0.0322   0.1268   0.0666   0.0203   0.3530   1.0000 
             |   0.2172   0.1161   0.0000   0.0011   0.3203   0.0000
             |
citetopprac3 |  -0.0202   0.1699   0.0952   0.5062   0.0143   0.0657  -0.0013 
             |   0.3233   0.0000   0.0000   0.0000   0.4852   0.0013   0.9510
             |
     citeage |   0.1356   0.1454   0.0054   0.2046   0.0762  -0.0457   0.0321 
             |   0.0007   0.0003   0.8945   0.0000   0.0590   0.2583   0.4270
             |

             | citet~c3  citeage
-------------+------------------
citetopprac3 |   1.0000 
             |
             |
     citeage |  -0.0125   1.0000 
             |   0.7572
             |

------------------------------------------------------------------------------------------------------------------------
-> indsimpletype = 7

             | grant_~e     cite citetopq citeec~s   citeit citeec~q citetop3
-------------+---------------------------------------------------------------
  grant_date |   1.0000 
             |
             |
        cite |   0.0020   1.0000 
             |   0.7917
             |
    citetopq |   0.0269   0.8498   1.0000 
             |   0.0005   0.0000
             |
 citeeconbus |  -0.0053   0.4288   0.4666   1.0000 
             |   0.4940   0.0000   0.0000
             |
      citeit |   0.0002   0.9546   0.7909   0.2048   1.0000 
             |   0.9759   0.0000   0.0000   0.0000
             |
citeeconbu~q |   0.0039   0.3365   0.4953   0.8249   0.1573   1.0000 
             |   0.6132   0.0000   0.0000   0.0000   0.0000
             |
    citetop3 |  -0.0083   0.2091   0.2981   0.6551   0.0646   0.8002   1.0000 
             |   0.2797   0.0000   0.0000   0.0000   0.0000   0.0000
             |
citetopprac3 |  -0.0218   0.1167   0.1447   0.4542   0.0153   0.4103   0.4310 
             |   0.0046   0.0000   0.0000   0.0000   0.0466   0.0000   0.0000
             |
     citeage |   0.1984   0.1256   0.0969   0.1347   0.0796   0.0990   0.1427 
             |   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000
             |

             | citet~c3  citeage
-------------+------------------
citetopprac3 |   1.0000 
             |
             |
     citeage |   0.0849   1.0000 
             |   0.0000
             |

. reg cite grant_date

      Source |       SS           df       MS      Number of obs   =    24,255
-------------+----------------------------------   F(1, 24253)     =      4.28
       Model |  465.923949         1  465.923949   Prob > F        =    0.0385
    Residual |  2639048.39    24,253  108.813276   R-squared       =    0.0002
-------------+----------------------------------   Adj R-squared   =    0.0001
       Total |  2639514.32    24,254     108.828   Root MSE        =    10.431

------------------------------------------------------------------------------
        cite | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
  grant_date |  -.0001024   .0000495    -2.07   0.039    -.0001995   -5.41e-06
       _cons |   4.305774   .9591549     4.49   0.000     2.425771    6.185776
------------------------------------------------------------------------------

. reg citeeconbus grant_date

      Source |       SS           df       MS      Number of obs   =    24,255
-------------+----------------------------------   F(1, 24253)     =     22.95
       Model |   143.98382         1   143.98382   Prob > F        =    0.0000
    Residual |   152174.99    24,253  6.27448109   R-squared       =    0.0009
-------------+----------------------------------   Adj R-squared   =    0.0009
       Total |  152318.974    24,254  6.28015889   Root MSE        =    2.5049

------------------------------------------------------------------------------
 citeeconbus | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
  grant_date |   -.000057   .0000119    -4.79   0.000    -.0000803   -.0000336
       _cons |   1.641636   .2303227     7.13   0.000      1.19019    2.093083
------------------------------------------------------------------------------

. reg citetop3 grant_date

      Source |       SS           df       MS      Number of obs   =    24,255
-------------+----------------------------------   F(1, 24253)     =     18.15
       Model |  3.51096752         1  3.51096752   Prob > F        =    0.0000
    Residual |  4690.63853    24,253  .193404467   R-squared       =    0.0007
-------------+----------------------------------   Adj R-squared   =    0.0007
       Total |  4694.14949    24,254  .193541251   Root MSE        =    .43978

------------------------------------------------------------------------------
    citetop3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
  grant_date |  -8.89e-06   2.09e-06    -4.26   0.000     -.000013   -4.80e-06
       _cons |   .2148713   .0404372     5.31   0.000     .1356119    .2941307
------------------------------------------------------------------------------

. reg citeage grant_date

      Source |       SS           df       MS      Number of obs   =     8,661
-------------+----------------------------------   F(1, 8659)      =    281.70
       Model |  12056.2902         1  12056.2902   Prob > F        =    0.0000
    Residual |  370595.755     8,659  42.7989092   R-squared       =    0.0315
-------------+----------------------------------   Adj R-squared   =    0.0314
       Total |  382652.045     8,660  44.1861484   Root MSE        =    6.5421

------------------------------------------------------------------------------
     citeage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
  grant_date |   .0009401    .000056    16.78   0.000     .0008303    .0010499
       _cons |  -9.303031   1.077922    -8.63   0.000    -11.41602   -7.190048
------------------------------------------------------------------------------

. reg cite grant_date fintech i.indsimple

      Source |       SS           df       MS      Number of obs   =    24,255
-------------+----------------------------------   F(5, 24249)     =     14.07
       Model |  7633.49161         5  1526.69832   Prob > F        =    0.0000
    Residual |  2631880.82    24,249  108.535644   R-squared       =    0.0029
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  2639514.32    24,254     108.828   Root MSE        =    10.418

-------------------------------------------------------------------------------
         cite | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
   grant_date |  -.0000382   .0000502    -0.76   0.447    -.0001366    .0000602
      fintech |  -.4646474   .1628931    -2.85   0.004     -.783928   -.1453668
              |
indsimpletype |
           2  |   .3535039   .3165147     1.12   0.264    -.2668845    .9738923
           5  |  -1.074109   .3372645    -3.18   0.001    -1.735168   -.4130495
           7  |   .5863395   .2733566     2.14   0.032     .0505437    1.122135
              |
        _cons |   3.074715   1.027549     2.99   0.003     1.060656    5.088775
-------------------------------------------------------------------------------

. reg citeeconbus grant_date fintech i.indsimple

      Source |       SS           df       MS      Number of obs   =    24,255
-------------+----------------------------------   F(5, 24249)     =     66.26
       Model |  2053.09744         5  410.619488   Prob > F        =    0.0000
    Residual |  150265.876    24,249  6.19678652   R-squared       =    0.0135
-------------+----------------------------------   Adj R-squared   =    0.0133
       Total |  152318.974    24,254  6.28015889   Root MSE        =    2.4893

-------------------------------------------------------------------------------
  citeeconbus | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
   grant_date |  -.0000508    .000012    -4.23   0.000    -.0000743   -.0000273
      fintech |  -.1444267   .0389224    -3.71   0.000    -.2207171   -.0681364
              |
indsimpletype |
           2  |   .3748318   .0756295     4.96   0.000     .2265934    .5230702
           5  |  -.5914472   .0805875    -7.34   0.000    -.7494036   -.4334907
           7  |  -.2998073   .0653171    -4.59   0.000    -.4278328   -.1717818
              |
        _cons |   1.848119   .2455272     7.53   0.000      1.36687    2.329367
-------------------------------------------------------------------------------

. reg citetop3 grant_date fintech i.indsimple

      Source |       SS           df       MS      Number of obs   =    24,255
-------------+----------------------------------   F(5, 24249)     =     33.10
       Model |  31.8170864         5  6.36341728   Prob > F        =    0.0000
    Residual |  4662.33241    24,249  .192269059   R-squared       =    0.0068
-------------+----------------------------------   Adj R-squared   =    0.0066
       Total |  4694.14949    24,254  .193541251   Root MSE        =    .43848

-------------------------------------------------------------------------------
     citetop3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
   grant_date |  -8.24e-06   2.11e-06    -3.90   0.000    -.0000124   -4.10e-06
      fintech |  -.0359582    .006856    -5.24   0.000    -.0493964     -.02252
              |
indsimpletype |
           2  |   .0663352   .0133218     4.98   0.000     .0402237    .0924467
           5  |  -.0342258   .0141951    -2.41   0.016    -.0620491   -.0064025
           7  |   -.012408   .0115053    -1.08   0.281    -.0349591    .0101431
              |
        _cons |   .2328686   .0432485     5.38   0.000     .1480989    .3176384
-------------------------------------------------------------------------------

. reg citeage grant_date fintech i.indsimple

      Source |       SS           df       MS      Number of obs   =     8,661
-------------+----------------------------------   F(5, 8655)      =     66.92
       Model |  14242.7664         5  2848.55328   Prob > F        =    0.0000
    Residual |  368409.278     8,655  42.5660634   R-squared       =    0.0372
-------------+----------------------------------   Adj R-squared   =    0.0367
       Total |  382652.045     8,660  44.1861484   Root MSE        =    6.5243

-------------------------------------------------------------------------------
      citeage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
   grant_date |   .0009841   .0000563    17.46   0.000     .0008737    .0010946
      fintech |  -.3139246   .1661305    -1.89   0.059    -.6395799    .0117307
              |
indsimpletype |
           2  |   .5947055   .3130442     1.90   0.057    -.0189356    1.208347
           5  |  -1.062679    .375411    -2.83   0.005    -1.798574   -.3267844
           7  |   .7261126   .2786491     2.61   0.009      .179894    1.272331
              |
        _cons |  -10.43386    1.12367    -9.29   0.000    -12.63652   -8.231195
-------------------------------------------------------------------------------

. 
. bys fintech:sum cite citetopq citeeconbus citeit citeeconbustopq citetop3 citetopprac3 citeage 

------------------------------------------------------------------------------------------------------------------------
-> fintech = 0

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        cite |      5,368    2.782414    11.33511          0        328
    citetopq |      5,368    .3222802    1.319929          0         33
 citeeconbus |      5,368    .7175857    2.367009          0         52
      citeit |      5,368    1.418778     8.88601          0        274
citeeconbu~q |      5,368    .1141952    .5685697          0         14
-------------+---------------------------------------------------------
    citetop3 |      5,368    .0780551    .5078653          0         10
citetopprac3 |      5,368    .0488077    .3573113          0         13
     citeage |      2,074    9.088276    6.377227        -13         51

------------------------------------------------------------------------------------------------------------------------
-> fintech = 1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        cite |     18,887    2.196114    10.15734          0        335
    citetopq |     18,887    .2590671    1.373363          0         35
 citeeconbus |     18,887    .4908138    2.541972          0         85
      citeit |     18,887    1.271562    7.810955          0        280
citeeconbu~q |     18,887    .0638534    .5274922          0         17
-------------+---------------------------------------------------------
    citetop3 |     18,887    .0330386    .4180979          0         20
citetopprac3 |     18,887    .0238259    .3039921          0         17
     citeage |      6,587     8.64361    6.727001        -15        146


. 
. gen appyrearly=(app_year<2005)

. gen appyrmid=(app_year>=2005 & app_year<2010)

. gen appyrlate=(app_year>=2010 & app_year<2015)

. gen appyrlatest=(app_year>=2015)

. gen citeearly=cite*appyrearly

. gen citemid=cite*appyrmid

. gen citelate=cite*appyrlate

. gen citelatest=cite*appyrlatest

. 
. * Table 7, Panel B
. 
. reg weighted citeearly-citelatest b3.apptype b5.industrytype us app_year global_sifi public vc_backed noncorporate rev
> enue age academic, vce(r)

Linear regression                               Number of obs     =     13,256
                                                F(21, 13234)      =      44.92
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1004
                                                Root MSE          =     3.2927

------------------------------------------------------------------------------
             |               Robust
weighted_c~e | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   citeearly |   .0114484   .0034401     3.33   0.001     .0047054    .0181914
     citemid |   .0223798   .0053377     4.19   0.000     .0119171    .0328424
    citelate |   .0856592   .0157682     5.43   0.000     .0547513    .1165671
  citelatest |   .5551668   .1682099     3.30   0.001     .2254512    .8848824
             |
     apptype |
   payments  |  -.0985184   .0637279    -1.55   0.122    -.2234342    .0263975
    banking  |  -.0721479   .0843351    -0.86   0.392    -.2374568    .0931609
             |
industrytype |
       bank  |  -.2820688   .0942754    -2.99   0.003     -.466862   -.0972755
     capmkt  |  -.9941848    .083957   -11.84   0.000    -1.158753    -.829617
    consfin  |    .136529   .1140442     1.20   0.231     -.087014    .3600719
      insur  |   1.587509   .2195585     7.23   0.000     1.157143    2.017875
         it  |  -.0875825   .0861697    -1.02   0.309    -.2564876    .0813225
   otherind  |   .1619522   .2066336     0.78   0.433    -.2430794    .5669837
             |
          us |   .5546538   .0562832     9.85   0.000     .4443306     .664977
    app_year |  -.0137745   .0069458    -1.98   0.047    -.0273893   -.0001596
 global_sifi |   .5548435   .0713053     7.78   0.000     .4150749    .6946122
      public |  -.4792344   .1113589    -4.30   0.000    -.6975137   -.2609551
   vc_backed |   .8735209   .1970205     4.43   0.000     .4873325    1.259709
noncorporate |  -.2698694   .2308922    -1.17   0.243    -.7224513    .1827124
     revenue |  -.6837039   .5621908    -1.22   0.224    -1.785678    .4182705
 age_of_firm |  -.0050007   .0005603    -8.93   0.000    -.0060988   -.0039025
    academic |  -1.561631   .2017417    -7.74   0.000    -1.957074   -1.166189
       _cons |   29.17159   13.93737     2.09   0.036     1.852341    56.49084
------------------------------------------------------------------------------

. reg kogan citeearly-citelatest b3.apptype b5.industrytype us app_year global_sifi public vc_backed noncorporate revenu
> e age academic, vce(r)

Linear regression                               Number of obs     =      9,173
                                                F(20, 9151)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3015
                                                Root MSE          =     91.027

------------------------------------------------------------------------------
             |               Robust
kogan_etal~l | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   citeearly |   1.029319   .4437339     2.32   0.020     .1595011    1.899136
     citemid |     .92538   .2976642     3.11   0.002     .3418917    1.508868
    citelate |   .3630767   .1345445     2.70   0.007     .0993395    .6268139
  citelatest |   2.132199   1.106951     1.93   0.054    -.0376729    4.302071
             |
     apptype |
   payments  |   2.493537   2.109954     1.18   0.237    -1.642444    6.629518
    banking  |    1.47145   2.608322     0.56   0.573    -3.641444    6.584344
             |
industrytype |
       bank  |   -36.0565   7.237399    -4.98   0.000    -50.24341   -21.86958
     capmkt  |  -66.74044   3.728051   -17.90   0.000    -74.04825   -59.43263
    consfin  |  -37.14486   3.662316   -10.14   0.000    -44.32381    -29.9659
      insur  |  -68.58223   5.039149   -13.61   0.000    -78.46009   -58.70438
         it  |  -93.28852   2.736495   -34.09   0.000    -98.65266   -87.92438
   otherind  |  -64.28303   3.538909   -18.16   0.000    -71.22008   -57.34598
             |
          us |   10.68679   1.521543     7.02   0.000     7.704227    13.66936
    app_year |    -2.8636   .3051755    -9.38   0.000    -3.461812   -2.265388
 global_sifi |   101.7619   5.993448    16.98   0.000     90.01344    113.5104
      public |   25.86436   2.438141    10.61   0.000     21.08506    30.64366
   vc_backed |  -21.07431   4.701047    -4.48   0.000    -30.28941   -11.85921
noncorporate |   -25.6359   3.122996    -8.21   0.000    -31.75767   -19.51413
     revenue |   247.4479    36.2416     6.83   0.000     176.4063    318.4896
 age_of_firm |   .0396563   .0193296     2.05   0.040     .0017661    .0775466
    academic |  -7.227497   1.847422    -3.91   0.000    -10.84886   -3.606138
       _cons |   5808.018   611.8506     9.49   0.000     4608.654    7007.381
------------------------------------------------------------------------------

. clear 

. 
. ** Importing all the academic cites
. 
. use finaccites

. 
. ** Number of journals--Table A-10
. 
. by journalid, sort: egen count=count(app_year) 

. sort journalid

. by journalid: drop if _n~=1
(54,250 observations deleted)

. sort count

. list journalid count in -20/l

      +--------------------+
      |  journalid   count |
      |--------------------|
2145. |  170137484     145 |
2146. |  193228710     156 |
2147. |  137519996     169 |
2148. |  116483603     173 |
2149. |  149240962     197 |
      |--------------------|
2150. |  157921468     206 |
2151. |   33323087     213 |
2152. |   66124381     216 |
2153. |  112676551     238 |
2154. |  106296714     242 |
      |--------------------|
2155. |   12529635     246 |
2156. | 2765043126     277 |
2157. | 2751751161     281 |
2158. |  143806524     288 |
2159. |  178916657     367 |
      |--------------------|
2160. |  162525099     381 |
2161. |   72684844     499 |
2162. |    5353659     701 |
2163. |  103482838    1166 |
2164. |         NA   32812 |
      +--------------------+

. 
. 
. 
. 
. *** CENSUSTABLE2.TXT
. 
. clear all

. set more 1

. 
. * Use to make Table 5 (patent data only) and Figure 4, Panel A
. 
. * Gross output
. 
. import excel using "Gross Output Final.xlsx", firstrow sheet("Ready")
(14 vars, 23 obs)

. gen year2=real(year)

. drop year

. ren year2 year

. drop if year<2000 | year==2019
(4 observations deleted)

. replace count328=count328+count339+count340+count342
(19 real changes made)

. replace count332=count332+count333+count334
(19 real changes made)

. drop count339 count340 count342 count333 count334 count341

. gen group=2000 if year>=2000 & year<=2004
(14 missing values generated)

. replace group=2005 if year>=2005 & year<=2009
(5 real changes made)

. replace group=2010 if year>=2010 & year<=2014
(5 real changes made)

. replace group=2015 if year>=2015 & year<=2018
(4 real changes made)

. foreach v of varlist count328-count999 {
  2.     by group, sort: egen `v'5yr=sum(`v')
  3.   } 

. keep group count3285yr-count9995yr

. by group, sort: drop if _n~=1
(15 observations deleted)

. list

     +------------------------------------------------------------------------------------+
     | group   cou~85yr   co~295yr   cou~05yr   cou~15yr   cou~25yr   cou~55yr   count9~r |
     |------------------------------------------------------------------------------------|
  1. |  2000     2451.1     2092.6      966.9     1099.6     2762.1        509      601.9 |
  2. |  2005     2677.5     2287.4     1263.7     1219.5       3499      589.3      675.1 |
  3. |  2010     2846.8     2160.4     1377.4     1047.9       3963      628.9      793.8 |
  4. |  2015     2332.6       1706     1135.3      874.6     4187.7      526.4      754.3 |
     +------------------------------------------------------------------------------------+

. 
. * Patents by field of use
. 
. clear all

. use financial_patent_data_v3

. gen rowtotal=accounting+investment_banking+commercial_banking+payments+cryptocurrency+currency+insurance+real_estate+r
> etail+wealth_management+security+communications

. sum rowtotal, d

                          rowtotal
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%            1              1
10%            1              1       Obs              24,255
25%            1              1       Sum of wgt.      24,255

50%            1                      Mean                  1
                        Largest       Std. dev.             0
75%            1              1
90%            1              1       Variance              0
95%            1              1       Skewness              .
99%            1              1       Kurtosis              .

. drop rowtotal

. 
. ** Adding fund field 
. 
. ren patent_id patent

. sort patent

. merge 1:1 patent using FundPatents

    Result                      Number of obs
    -----------------------------------------
    Not matched                        24,203
        from master                    24,152  (_merge==1)
        from using                         51  (_merge==2)

    Matched                               103  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(51 observations deleted)

. gen passivefund=(_merge==3) & index==1

. gen activefund=(_merge==3) & index==0

. drop _merge index

. egen count=rowmax(accounting-wealth)

. replace count=1/count
(12,611 real changes made)

. tab count

      count |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |     11,644       48.01       48.01
          2 |      8,027       33.09       81.10
          3 |      3,090       12.74       93.84
          4 |        827        3.41       97.25
          5 |        281        1.16       98.41
          6 |        205        0.85       99.25
          7 |        125        0.52       99.77
          8 |         45        0.19       99.95
          9 |          8        0.03       99.99
         10 |          3        0.01      100.00
------------+-----------------------------------
      Total |     24,255      100.00

. foreach v of varlist accounting-wealth {
  2.     replace `v'=`v'*count/(count+1) if (passivefund==1 | activefund==1)
  3.   } 
(5 real changes made)
(57 real changes made)
(8 real changes made)
(6 real changes made)
(38 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(8 real changes made)
(42 real changes made)

. 
. replace activefund=activefund/(count+1)
(90 real changes made)

. replace passivefund=passivefund/(count+1)
(13 real changes made)

. 
. ** Figure 4, Panel A
. 
. sum accounting investment_banking commercial_banking payments cryptocurrency currency insurance real_estate retail wea
> lth_management security communications passivefund activefund

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  accounting |     24,255    .0420502    .1595549          0          1
investment~g |     24,255    .0777813    .2255633          0          1
commercial~g |     24,255    .0504517    .1684391          0          1
    payments |     24,255    .3727955    .3769091          0          1
cryptocurr~y |     24,255    .0115153    .0670557          0          1
-------------+---------------------------------------------------------
    currency |     24,255    .0057265    .0593467          0          1
   insurance |     24,255    .0132671    .0992131          0          1
 real_estate |     24,255    .0133779     .090717          0          1
retail_ban~g |     24,255    .0606465    .1807701          0          1
wealth_man~t |     24,255    .0137716    .0985412          0          1
-------------+---------------------------------------------------------
    security |     24,255    .1979463    .3110279          0          1
communicat~s |     24,255    .1389048    .2735971          0          1
 passivefund |     24,255    .0001993    .0088551          0         .5
  activefund |     24,255     .001566    .0263987          0         .5

. 
. gen rowtotal=accounting+investment_banking+commercial_banking+payments+cryptocurrency+currency+insurance+real_estate+r
> etail+wealth_management+security+communications+passivefund+activefund

. sum rowtotal, d

                          rowtotal
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%            1              1
10%            1              1       Obs              24,255
25%            1              1       Sum of wgt.      24,255

50%            1                      Mean                  1
                        Largest       Std. dev.             0
75%            1              1
90%            1              1       Variance              0
95%            1              1       Skewness              .
99%            1              1       Kurtosis              .

. drop rowtotal

. 
. ** Replacing security and communications--seperate conversion for each 5-year period
. 
. gen residual=communications+security

. 
. *** 2000-04
. 
. sum accounting-wealth if (security+communications>0) & app_year<2005 & app_year>=2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  accounting |      2,830    .0246356    .0882236          0         .5
investment~g |      2,830    .0273648    .0938374          0         .5
commercial~g |      2,830    .0335986    .1007865          0         .5
communicat~s |      2,830    .2659354    .3357298          0          1
    payments |      2,830    .1835662    .2045513          0         .5
-------------+---------------------------------------------------------
cryptocurr~y |      2,830    .0145685    .0726604          0         .5
    currency |      2,830    .0019831    .0256415          0         .5
   insurance |      2,830    .0024926    .0274619          0         .5
 real_estate |      2,830    .0064685     .042554          0         .5
retail_ban~g |      2,830      .03914    .1072847          0         .5
-------------+---------------------------------------------------------
    security |      2,830     .395707    .3474728          0          1
wealth_man~t |      2,830    .0040448    .0350334          0         .5

. 
. replace accounting=accounting+residual*.0246/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace investment_banking=investment_banking+residual*.0274/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace commercial_banking=commercial_banking+residual*.0336/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace payments=payments+residual*.1836/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace cryptocurrency=cryptocurrency+residual*.0146/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace currency=currency+residual*.0020/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace insurance=insurance+residual*.0025/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace real_estate=real_estate+residual*.0065/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace retail_banking=retail_banking+residual*.0391/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. replace wealth_management=wealth_management+residual*.0040/(1-.2659-.3957) if app_year<2005 & app_year>=2000
(2,830 real changes made)

. 
. *** 2005-09
. 
. sum accounting-wealth if (security+communications>0) & app_year<2010 & app_year>=2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  accounting |      3,658    .0243866    .0876893          0         .5
investment~g |      3,658    .0299698    .0962493          0         .5
commercial~g |      3,658    .0334364     .100476          0         .5
communicat~s |      3,658    .2473345    .3210268          0          1
    payments |      3,658    .1952826    .2103606          0         .5
-------------+---------------------------------------------------------
cryptocurr~y |      3,658    .0189793    .0849059          0         .5
    currency |      3,658    .0021312    .0220611          0         .5
   insurance |      3,658     .002852     .029174          0         .5
 real_estate |      3,658    .0061287    .0410905          0         .5
retail_ban~g |      3,658    .0365053    .1060212          0         .5
-------------+---------------------------------------------------------
    security |      3,658    .3978073    .3467467          0          1
wealth_man~t |      3,658    .0048675     .038195          0         .5

. 
. replace accounting=accounting+residual*.0244/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace investment_banking=investment_banking+residual*.0300/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace commercial_banking=commercial_banking+residual*.0334/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace payments=payments+residual*.1953/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace cryptocurrency=cryptocurrency+residual*.0190/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace currency=currency+residual*.0021/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace insurance=insurance+residual*.0029/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace real_estate=real_estate+residual*.0061/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace retail_banking=retail_banking+residual*.0365/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. replace wealth_management=wealth_management+residual*.0049/(1-.2474-.3979) if app_year<2010 & app_year>=2005
(3,658 real changes made)

. 
. *** 2010-14
. 
. sum accounting-wealth if (security+communications>0) & app_year<2015 & app_year>=2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  accounting |      4,554     .022222    .0837416          0         .5
investment~g |      4,554     .025829    .0917815          0         .5
commercial~g |      4,554    .0319239    .1009779          0         .5
communicat~s |      4,554    .2868013    .3370841          0          1
    payments |      4,554    .2164751    .2134424          0         .5
-------------+---------------------------------------------------------
cryptocurr~y |      4,554    .0224538    .0883865          0         .5
    currency |      4,554    .0019548    .0234304          0         .5
   insurance |      4,554     .002531    .0291022          0         .5
 real_estate |      4,554      .00482    .0358853          0         .5
retail_ban~g |      4,554    .0253763    .0892554          0         .5
-------------+---------------------------------------------------------
    security |      4,554    .3568055     .329867          0          1
wealth_man~t |      4,554    .0026059    .0288994          0         .5

. 
. replace accounting=accounting+residual*.0222/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace investment_banking=investment_banking+residual*.0258/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace commercial_banking=commercial_banking+residual*.0319/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace payments=payments+residual*.2165/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace cryptocurrency=cryptocurrency+residual*.0225/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace currency=currency+residual*.0020/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace insurance=insurance+residual*.0025/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace real_estate=real_estate+residual*.0048/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace retail_banking=retail_banking+residual*.0254/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. replace wealth_management=wealth_management+residual*.0026/(1-.2868-.3568) if app_year<2015 & app_year>=2010
(4,554 real changes made)

. 
. *** 2015-18
. 
. sum accounting-wealth if (security+communications>0) & app_year<2019 & app_year>=2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  accounting |      1,508    .0169832    .0742266          0         .5
investment~g |      1,508    .0138886    .0702311          0         .5
commercial~g |      1,508    .0308813    .1021009          0         .5
communicat~s |      1,508    .2690287    .3286673          0          1
    payments |      1,508    .2030914    .2168568          0         .5
-------------+---------------------------------------------------------
cryptocurr~y |      1,508    .0349643    .1111724          0         .5
    currency |      1,508    .0005921    .0104863          0        .25
   insurance |      1,508     .001747    .0250144          0         .5
 real_estate |      1,508    .0032857    .0310302          0         .5
retail_ban~g |      1,508    .0243053    .0851339          0         .5
-------------+---------------------------------------------------------
    security |      1,508    .3987179    .3441322          0          1
wealth_man~t |      1,508     .002017    .0259263          0         .5

. 
. replace accounting=accounting+residual*.0170/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace investment_banking=investment_banking+residual*.0139/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace commercial_banking=commercial_banking+residual*.0309/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace payments=payments+residual*.2031/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace cryptocurrency=cryptocurrency+residual*.0350/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace currency=currency+residual*.0006/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace insurance=insurance+residual*.0017/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace real_estate=real_estate+residual*.0033/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace retail_banking=retail_banking+residual*.0243/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. replace wealth_management=wealth_management+residual*.0020/(1-.2690-.3987) if app_year<2019 & app_year>=2015
(1,508 real changes made)

. 
. gen rowtotal=accounting+investment_banking+commercial_banking+payments+cryptocurrency+currency+insurance+real_estate+r
> etail+wealth_management+passivefund+activefund

. sum rowtotal, d

                          rowtotal
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .9984953       .9984953
 5%     .9985225       .9984953
10%     .9992477       .9984953       Obs              24,255
25%     .9996306       .9984953       Sum of wgt.      24,255

50%     .9999061                      Mean           .9997282
                        Largest       Std. dev.      .0004065
75%            1              1
90%            1              1       Variance       1.65e-07
95%            1              1       Skewness      -1.847215
99%            1              1       Kurtosis       5.732741

. drop rowtotal

. 
. ** Generating totals
. 
. gen count328=real_estate+payments

. gen count329=retail_banking+commercial_banking

. gen count330=currency+cryptocurrency+wealth_management+activefund

. gen count331=investment_banking

. gen count332=insurance

. gen count335=passivefund

. gen count999=accounting

. 
. foreach v of varlist count328-count999 {
  2.     by app_year, sort: egen `v'sum=sum(`v')
  3.   } 

. keep app_year count328sum-count999sum

. by app_year, sort: drop if _n~=1
(24,236 observations deleted)

. gen group=2000 if app_year>=2000 & app_year<=2004
(14 missing values generated)

. replace group=2005 if app_year>=2005 & app_year<=2009
(5 real changes made)

. replace group=2010 if app_year>=2010 & app_year<=2014
(5 real changes made)

. replace group=2015 if app_year>=2015 & app_year<=2018
(4 real changes made)

. 
. foreach v of varlist count328sum-count999sum {
  2.     by group, sort: egen `v'5yr=sum(`v')
  3.   } 

. keep group count328sum5yr-count999sum5yr

. by group, sort: drop if _n~=1
(15 observations deleted)

. 
. ** Table 5 (patent only)
. 
. list

     +------------------------------------------------------------------------------------+
     | group   c~8sum~r   count3..   c~0sum~r   c~1sum~r   c~2sum~r   c~5sum~r   count9~r |
     |------------------------------------------------------------------------------------|
  1. |  2000   2955.551   1045.484   283.1728   574.2532   58.25373   1.166667    396.353 |
  2. |  2005   4316.951   1374.785   417.2658   855.4644   105.1295          2   491.7399 |
  3. |  2010   5390.922   1383.691   507.3671   928.1106   151.4287   1.416667    516.419 |
  4. |  2015    1540.45   396.5595   206.1826   134.2649   65.81934        .25   147.9588 |
     +------------------------------------------------------------------------------------+

. 
. 
. 
. 
. 
. *** FINPATCSA2.TXT
. 
. set more off

. clear 

. 
. 
. use csa_year_data

. 
. * Produces Table 8, A-14, and A-21
. 
. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    app_year |      3,380      2009.5    5.767134       2000       2019
    csa_code |      3,380    338.3905    126.8634        104        566
   csa_title |          0
  population |      3,320     1366996     2713751      32874   2.39e+07
  households |      3,320    504323.1    955183.9      12936    8516016
-------------+---------------------------------------------------------
median_hh_~e |      3,320    46803.98    9187.017    24062.7      96998
establishm~s |      3,320     2121.63     4042.51         74      35103
   employees |      3,120    32372.93    73215.51        301     719385
adult_popu~n |      3,320    905433.1     1809084      21671   1.66e+07
adult_pop_~s |      3,320      277346    627511.6       6225    6632190
-------------+---------------------------------------------------------
   n_patents |      3,380     4.60858    20.21586          0        334
weighted_c~e |      3,380    6.398233    33.46998          0   772.2792
kogan_etal~l |      3,380    5.613366    106.4108          0   4520.604
kelly_eta~10 |      3,380    2.184259     13.8793          0    515.541
kelly_etal~5 |      3,380    1.247305    6.933314          0   230.8097
-------------+---------------------------------------------------------
  accounting |      3,380    .1929824    .9380104          0     17.075
investment~g |      3,380    .4124591    2.749743          0   54.75952
commercial~g |      3,380    .2320999    1.204626          0   22.17024
communica~ns |      3,380    .6011137    2.813776          0   55.56667
    payments |      3,380     1.74525     7.88827          0   144.8083
-------------+---------------------------------------------------------
cryptocurr~y |      3,380    .0544537    .3404926          0   6.366667
    currency |      3,380    .0279553    .2275852          0   4.058333
   insurance |      3,380    .0647086    .4423307          0      15.75
 real_estate |      3,380    .0745352    .4533096          0          9
retail_ban~g |      3,380    .2773235    1.104981          0   14.85833
-------------+---------------------------------------------------------
    security |      3,380    .8548756    3.945919          0   78.18333
wealth_man~t |      3,380    .0708228    .4429355          0      8.125
communica~ts |      3,380    .1819527    1.257484          0         30
consumer_d~s |      3,380    .2097633    1.559349          0         38
consumer_s~s |      3,380    .0156805    .4005652          0         22
-------------+---------------------------------------------------------
energy_n_p~s |      3,380    .0038462    .0665161          0          2
financials~s |      3,380    1.077219    6.368409          0        117
health_car~s |      3,380    .0248521    .2189001          0          5
industrial~s |      3,380    .1269231    .7574333          0         18
informatio~s |      3,380    1.857988    9.906904          0        198
-------------+---------------------------------------------------------
materials_~s |      3,380    .0026627    .0569939          0          2
real_estat~s |      3,380    .0026627    .0619693          0          2
utilities_~s |      3,380    .0005917    .0243216          0          1
communicat~_ |      3,380    .4421038    4.563874          0   117.9068
consumer_d~_ |      3,380     .252563    2.160942          0   57.49337
-------------+---------------------------------------------------------
consumer_s~e |      3,380    .0144193    .2803205          0   9.570528
energy_wei~e |      3,380    .0036654    .1096545          0   4.799296
financials~e |      3,380    1.301523    15.05191          0   772.2792
health_car~e |      3,380    .0835273    1.610709          0   54.69445
industrial~e |      3,380    .1846913    1.581894          0   55.72709
-------------+---------------------------------------------------------
informatio~_ |      3,380    2.798059    18.50606          0   436.2282
materials_~e |      3,380    .0009054    .0334417          0   1.754635
real_est~ite |      3,380    .0036709    .1414379          0   7.911224
utilities_~e |      3,380    .0000724    .0042068          0   .2445759
banks_n_pa~s |      3,380    .3650888    2.586502          0         72
-------------+---------------------------------------------------------
capital_ma~s |      3,380    .3837278    3.510324          0         72
consumer_f~s |      3,380    .1008876    1.015214          0         27
diversifie~n |      3,380    .0260355    .2503084          0          7
insurance_~s |      3,380    .1609467    1.390413          0         54
thrifts_mo~n |      3,380    .0405325    .6095441          0         15
-------------+---------------------------------------------------------
banks_weig~e |      3,380    .3853702    2.921702          0   64.96134
capital_ma~e |      3,380    .1478021    1.331445          0   35.10248
consumer_f~e |      3,380    .1124647    1.273528          0   40.06008
diversifie~w |      3,380    .0390359     .767371          0    31.1338
insurance_~e |      3,380    .5895696     14.3071          0   772.2792
-------------+---------------------------------------------------------
thrifts_mo~e |      3,380    .0272802    .5173418          0    20.9901
vc_num_deals |      2,869    31.06065    139.6026          0       2306
vc_sum_equ~d |      2,869    321.6151    1998.151          0   55689.49
us_ai_rank~g |        120         3.5    1.714986          1          6

. 
. * Clean-up
. 
. ** Replacing missing VC variables
. 
. replace vc_num_deals=0 if vc_num_deals==.
(511 real changes made)

. replace vc_sum_equity_invested=0 if vc_sum_equity_invested==.
(511 real changes made)

. 
. ** Creating demographic share variable
. 
. gen empshare=employees/adult_population
(260 missing values generated)

. replace empshare=0 if employees==.
(260 real changes made)

. gen collegeshare=adult_pop_bachelors/adult_population
(60 missing values generated)

. 
. ** Dropping Puerto Rican CSAs & 2019
. 
. drop if csa_code==364
(20 observations deleted)

. drop if csa_code==434
(20 observations deleted)

. drop if csa_code==490
(20 observations deleted)

. drop if app_year==2019
(166 observations deleted)

. 
. ** Merging in region
. 
. *** Associating CSA with states
. 
. save csa_year_data_temp, replace
file csa_year_data_temp.dta saved

. import delimited csa.csv, clear
(encoding automatically selected: ISO-8859-1)
(7 vars, 166 obs)

. save temp, replace
file temp.dta saved

. use csa_year_data_temp

. merge m:1 csa_code using temp, keepusing(state)

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                             3,154  (_merge==3)
    -----------------------------------------

. drop _merge

. 
. *** Associating states with regions
. 
. save csa_year_data_temp, replace
file csa_year_data_temp.dta saved

. import delimited state.csv, clear varn(1)
(encoding automatically selected: ISO-8859-1)
(4 vars, 51 obs)

. save temp, replace
file temp.dta saved

. use csa_year_data_temp

. merge m:1 state using temp, keepusing(division)

    Result                      Number of obs
    -----------------------------------------
    Not matched                            10
        from master                         0  (_merge==1)
        from using                         10  (_merge==2)

    Matched                             3,154  (_merge==3)
    -----------------------------------------

. drop _merge

. 
. ** Coding CSAs with financial VC in 2000
. 
. gen Sum2000FinVC=117.94 if csa_code==122
(3,145 missing values generated)

. replace Sum2000FinVC= 233.92 if csa_code==148
(19 real changes made)

. replace Sum2000FinVC= 74.09 if csa_code==176
(19 real changes made)

. replace Sum2000FinVC= 0.62 if csa_code==194
(19 real changes made)

. replace Sum2000FinVC= 0.10 if csa_code==198
(19 real changes made)

. replace Sum2000FinVC= 561.22 if csa_code==206
(19 real changes made)

. replace Sum2000FinVC= 600.00 if csa_code==216
(19 real changes made)

. replace Sum2000FinVC= 100.25 if csa_code==220
(19 real changes made)

. replace Sum2000FinVC= 1.68 if csa_code==294
(19 real changes made)

. replace Sum2000FinVC= 0.10 if csa_code==300
(19 real changes made)

. replace Sum2000FinVC= 6.00 if csa_code==312
(19 real changes made)

. replace Sum2000FinVC= 16.00 if csa_code==336
(19 real changes made)

. replace Sum2000FinVC= 41.86 if csa_code==348
(19 real changes made)

. replace Sum2000FinVC= 54.06 if csa_code==370
(19 real changes made)

. replace Sum2000FinVC= 0.50 if csa_code==400
(19 real changes made)

. replace Sum2000FinVC= 4.00 if csa_code==406
(19 real changes made)

. replace Sum2000FinVC= 232.70 if csa_code==408
(19 real changes made)

. replace Sum2000FinVC= 6.00 if csa_code==412
(19 real changes made)

. replace Sum2000FinVC= 15.00 if csa_code==416
(19 real changes made)

. replace Sum2000FinVC= 16.00 if csa_code==422
(19 real changes made)

. replace Sum2000FinVC= 3.74 if csa_code==426
(19 real changes made)

. replace Sum2000FinVC= 36.00 if csa_code==428
(19 real changes made)

. replace Sum2000FinVC= 74.70 if csa_code==430
(19 real changes made)

. replace Sum2000FinVC= 0.11 if csa_code==440
(19 real changes made)

. replace Sum2000FinVC= 0.50 if csa_code==450
(19 real changes made)

. replace Sum2000FinVC= 4.30 if csa_code==476
(19 real changes made)

. replace Sum2000FinVC= 19.50 if csa_code==482
(19 real changes made)

. replace Sum2000FinVC= 1107.68 if csa_code==488
(19 real changes made)

. replace Sum2000FinVC= 30.45 if csa_code==500
(19 real changes made)

. replace Sum2000FinVC= 0.80 if csa_code==545
(19 real changes made)

. replace Sum2000FinVC= 0 if Sum2000FinVC==.
(2,594 real changes made)

. 
. ** Making 5-year periods
. 
. gen app_period=2000 if app_year>=2000 & app_year<=2004
(2,334 missing values generated)

. replace app_period=2005 if app_year>=2005 & app_year<=2009
(830 real changes made)

. replace app_period=2010 if app_year>=2010 & app_year<=2014
(830 real changes made)

. replace app_period=2015 if app_year>=2015 & app_year<=2019
(664 real changes made)

. drop if app_period==.
(10 observations deleted)

. 
. ** Generating unweighted and weighted patenting in total, by revenue, Sifi, application, and industry
. 
. save csa_year_data_temp, replace
file csa_year_data_temp.dta saved

. use financial_patent_data_v3

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   patent_id |     24,255     8447202    921178.4    6173891   1.02e+07
    app_date |     24,255    17955.64    1681.123      14612      21447
    app_year |     24,255    2008.652    4.611431       2000       2018
  grant_date |     24,255    19326.14    1352.905      14991      21606
 primary_cpc |          0
-------------+---------------------------------------------------------
cpc_subclass |          0
  cite_count |     24,255    12.07607    31.09662          0        601
  mean_cites |     24,255    10.69635    13.40186          0   163.1282
weighted_c~e |     24,252    1.249208    3.446227          0   102.0472
assignee_t~e |     22,365    2.199955    .4481624          2          7
-------------+---------------------------------------------------------
kogan_etal~l |      9,499    53.60786    107.2379   .0006292   1940.746
kelly_eta~10 |     18,155    1.335914    1.040012          0   8.988219
kelly_etal~5 |     18,155    .8571892     .472032          0   3.978838
       state |          0
  state_fips |     19,153    24.71232    16.22884          1         78
-------------+---------------------------------------------------------
    csa_code |     15,577    356.7765    136.5198        104        566
   csa_title |          0
inventor_1~y |          0
assignee_1~y |          0
vc_num_deals |     15,441    459.9734    562.5651          0       2306
-------------+---------------------------------------------------------
vc_sum_equ~d |     15,441    4872.898    7419.168          0   55689.49
us_ai_rank~g |      8,085    2.396908      1.6098          1          6
  accounting |     24,255    .0420914    .1596893          0          1
investment~g |     24,255    .0785083    .2274502          0          1
commercial~g |     24,255    .0504765    .1684729          0          1
-------------+---------------------------------------------------------
communicat~s |     24,255    .1389632    .2737019          0          1
    payments |     24,255    .3731844    .3771753          0          1
cryptocurr~y |     24,255    .0115153    .0670557          0          1
    currency |     24,255    .0057265    .0593467          0          1
   insurance |     24,255    .0132671    .0992131          0          1
-------------+---------------------------------------------------------
 real_estate |     24,255    .0133779     .090717          0          1
retail_ban~g |     24,255    .0606465    .1807701          0          1
    security |     24,255    .1979814    .3110459          0          1
wealth_man~t |     24,255    .0142615    .1015904          0          1
pae_initia~t |     24,255    .0176458    .1316631          0          1
-------------+---------------------------------------------------------
assignee_1~e |          0
pae_reassi~t |     24,255    .0109256    .1039551          0          1
reassignme~e |          0
pae_reassi~e |        265    18763.75    1303.724      14650      21137
    capiq_id |          0
-------------+---------------------------------------------------------
company_name |          0
     revenue |     13,346    29808.75    42680.09          0     485651
      ebitda |     10,353    5460.739    8671.517     -13595      82487
  rd_expense |      5,629    2099.578    2818.713     .05687      28837
advertisin~e |      6,281    765.7837    1072.822       .001   11541.87
-------------+---------------------------------------------------------
  net_income |     13,438    3141.358    6247.718     -99289      53394
        cash |     13,192     16046.1    48444.66    -.04757     331285
long_term_~t |     10,625    49249.73    144512.4    -5.9612    2944357
short_term~t |      8,184    57247.24    118859.5          0    1099811
short_term~s |      9,401    34604.06    105264.5          0     824318
-------------+---------------------------------------------------------
shareholde~y |     13,234    30338.87    53621.34     -50391     267146
  market_cap |     11,411    69433.16    86006.04     .00821   860882.5
  employment |     12,173    93562.38    174450.2          7    2300000
year_founded |     17,659    1945.101    59.14909       1727       2018
 age_of_firm |     17,659    73.89943    59.14909          1        292
-------------+---------------------------------------------------------
 global_sifi |     24,255    .0627912     .242592          0          1
primary_in~y |          0
primary_in~e |          0
gics_secto~e |          0
gics_group~e |          0
-------------+---------------------------------------------------------
gics_indus~e |          0
 gics_sector |          0
gics_indus~s |          0
revenue_gr~p |          0
      public |     24,255    .4704597    .4991369          0          1
-------------+---------------------------------------------------------
   vc_backed |     24,255    .0496392     .217203          0          1
          bs |     23,197    813884.3    450114.8        580    2377940
          fs |     23,197    782923.3    436854.3          0    2374299
    division |          0

. sort csa_code app_year

. 
. ** Orphans
. 
. gen app_period=2000 if app_year>=2000 & app_year<=2004
(18,938 missing values generated)

. replace app_period=2005 if app_year>=2005 & app_year<=2009
(7,564 real changes made)

. replace app_period=2010 if app_year>=2010 & app_year<=2014
(8,881 real changes made)

. replace app_period=2015 if app_year>=2015 & app_year<=2019
(2,493 real changes made)

. drop if app_period==.
(0 observations deleted)

. tab app_period, sum(weighted)

            |      Summary of weighted_cite
 app_period |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   1.1781558   1.9763926       5,317
       2005 |   1.1478377   2.7605497       7,564
       2010 |   1.2914965   3.9208353       8,880
       2015 |   1.5579336   5.4057237       2,491
------------+------------------------------------
      Total |   1.2492083    3.446227      24,252

. tab app_period, sum(kogan)

            |      Summary of kogan_etal_val
 app_period |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   56.736495   139.71751       2,147
       2005 |    53.06346   117.73941       3,028
       2010 |   51.092367   76.573279       3,416
       2015 |   57.489096   76.382179         908
------------+------------------------------------
      Total |   53.607857   107.23787       9,499

. tab app_period if inventor=="US" & csa_code==., sum(weighted)

            |      Summary of weighted_cite
 app_period |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   1.2955919   2.0587963         703
       2005 |   1.2638349   2.7415769       1,280
       2010 |   1.4270631   4.0927651       1,272
       2015 |   2.1551929   8.3054218         320
------------+------------------------------------
      Total |   1.4079429   3.9618426       3,575

. tab app_period if inventor=="US" & csa_code==., sum(kogan)

            |      Summary of kogan_etal_val
 app_period |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   68.304637   168.90091         285
       2005 |   47.486154   121.24455         463
       2010 |   46.872229   70.788337         470
       2015 |   57.131671    85.35447         114
------------+------------------------------------
      Total |   52.549451   116.82915       1,332

. tab app_period if inventor~="US", sum(weighted)

            |      Summary of weighted_cite
 app_period |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   .73704518   1.5730661       1,429
       2005 |   .69356719   2.6822059       1,510
       2010 |   .66441438   2.1453209       1,616
       2015 |   .66081925   2.1916794         546
------------+------------------------------------
      Total |   .69300627   2.1893303       5,101

. tab app_period if inventor~="US", sum(kogan)

            |      Summary of kogan_etal_val
 app_period |        Mean   Std. dev.       Freq.
------------+------------------------------------
       2000 |   11.855517   50.841225         583
       2005 |   21.795847   55.538535         525
       2010 |   34.878944   61.127812         542
       2015 |   42.658515   63.021282         158
------------+------------------------------------
      Total |   24.335741     57.4943       1,808

. 
. *** Total patents
. 
. egen csapatcount=count(patent_id), by(csa_code app_year)

. egen csawtpatcount=sum(weighted_cite), by(csa_code app_year)

. egen csakoganpatcount=sum(kogan_etal_val), by(csa_code app_year)

. 
. *** Revenue category
. 
. gen small=(revenue_group=="Small")

. gen smallwt=weighted_cite*small
(3 missing values generated)

. gen smallkogan=kogan_etal_val*small
(14,756 missing values generated)

. egen csapatcount_small=sum(small), by(csa_code app_year)

. egen csawtpatcount_small=sum(smallwt), by(csa_code app_year)

. egen csakoganpatcount_small=sum(smallkogan), by(csa_code app_year)

. drop small smallwt smallkogan

. gen medium=(revenue_group=="Medium")

. gen mediumwt=weighted_cite*medium
(3 missing values generated)

. gen mediumkogan=kogan_etal_val*medium
(14,756 missing values generated)

. egen csapatcount_medium=sum(medium), by(csa_code app_year)

. egen csawtpatcount_medium=sum(mediumwt), by(csa_code app_year)

. egen csakoganpatcount_medium=sum(mediumkogan), by(csa_code app_year)

. drop medium mediumwt mediumkogan

. gen large=(revenue_group=="Large")

. gen largewt=weighted_cite*large
(3 missing values generated)

. gen largekogan=kogan_etal_val*large
(14,756 missing values generated)

. egen csapatcount_large=sum(large), by(csa_code app_year)

. egen csawtpatcount_large=sum(largewt), by(csa_code app_year)

. egen csakoganpatcount_large=sum(largekogan), by(csa_code app_year)

. drop large largewt largekogan

. 
. *** Sifi status
. 
. gen sifiwt=weighted_cite*global_sifi
(3 missing values generated)

. gen sifikogan=kogan_etal_val* global_sifi 
(14,756 missing values generated)

. egen csapatcount_sifi=sum(global_sifi), by(csa_code app_year)

. egen csawtpatcount_sifi=sum(sifiwt), by(csa_code app_year)

. egen csakoganpatcount_sifi=sum(sifikogan), by(csa_code app_year)

. drop sifiwt sifikogan

. gen nonsifi=(global_sifi==0)

. gen nonsifiwt=weighted_cite*nonsifi
(3 missing values generated)

. gen nonsifikogan=kogan_etal_val*nonsifi
(14,756 missing values generated)

. egen csapatcount_nonsifi=sum(nonsifi), by(csa_code app_year)

. egen csawtpatcount_nonsifi=sum(nonsifiwt), by(csa_code app_year)

. egen csakoganpatcount_nonsifi=sum(nonsifikogan), by(csa_code app_year)

. drop nonsifi nonsifiwt nonsifikogan

. 
. *** Three broad applications
. 
. gen paymentswt=weighted_cite*payments
(3 missing values generated)

. gen paymentskogan=kogan_etal_val* payments 
(14,756 missing values generated)

. egen csapatcount_payments=sum(payments), by(csa_code app_year)

. egen csawtpatcount_payments=sum(paymentswt), by(csa_code app_year)

. egen csakoganpatcount_payments=sum(paymentskogan), by(csa_code app_year)

. drop paymentswt paymentskogan

. gen banking=(commercial_banking==1 | investment_banking==1 | retail_banking==1)

. gen bankingwt=weighted_cite*banking
(3 missing values generated)

. gen bankingkogan=kogan_etal_val* banking 
(14,756 missing values generated)

. egen csapatcount_banking=sum(banking), by(csa_code app_year)

. egen csawtpatcount_banking=sum(bankingwt), by(csa_code app_year)

. egen csakoganpatcount_banking=sum(bankingkogan), by(csa_code app_year)

. drop bankingwt bankingkogan

. gen other=(banking~=1 & payments~=1)

. gen otherwt=weighted_cite*other
(3 missing values generated)

. gen otherkogan=kogan_etal_val* other 
(14,756 missing values generated)

. egen csapatcount_other=sum(other), by(csa_code app_year)

. egen csawtpatcount_other=sum(otherwt), by(csa_code app_year)

. egen csakoganpatcount_other=sum(otherkogan), by(csa_code app_year)

. drop other otherwt otherkogan banking

. 
. *** Assignee industry 
. 
. **** Basic sorting
. 
. gen bank=(primary_industry=="Diversified Banks" | primary_industry=="Regional Banks" | primary_industry=="Thrifts and 
> Mortgage Finance")

. gen capmkt=(primary_industry=="Asset Management and Custody Banks" | primary_industry=="Diversified Capital Markets" |
>  primary_industry=="Diversified REITs" | primary_industry=="Financial Exchanges and Data" | primary_industry=="Investm
> ent Banking and Brokerage" | primary_industry=="Specialized REITs") 

. gen consfin=(primary_industry=="Consumer Finance" | primary_industry=="Specialized Finance")

. gen insur=(primary_industry=="Life and Health Insurance" | primary_industry=="Multi-line Insurance" | primary_industry
> =="Property and Casualty Insurance" | primary_industry=="Reinsurance")

. gen pay=(primary_industry=="Data Processing and Outsourced Services")

. gen it=(primary_industry=="Application Software" | primary_industry=="Communications Equipment" | primary_industry=="C
> onsumer Electronics" | primary_industry=="Electrical Components and Equipment" | primary_industry=="Electronic Compone
> nts")

. replace it=1 if (primary_industry=="IT Consulting and Other Services" | primary_industry=="Electronic Equipment and In
> struments" | primary_industry=="Electronic Manufacturing Services" | primary_industry=="Integrated Telecommunication S
> ervices" | primary_industry=="Interactive Media and Services")
(1,967 real changes made)

. replace it=1 if (primary_industry=="Internet Services and Infrastructure" | primary_industry=="Internet and Direct Mar
> keting Retail" | primary_industry=="Semiconductor Equipment" | primary_industry=="Semiconductors" | primary_industry==
> "Specialized Consumer Services" | primary_industry=="Systems Software")
(1,862 real changes made)

. replace it=1 if (primary_industry=="Technology Distributors" | primary_industry=="Technology Hardware, Storage and Per
> ipherals" | primary_industry=="Wireless Telecommunication Services")
(1,883 real changes made)

. gen otherind=(bank==0 & capmkt==0 & consfin==0 & insur==0 & pay==0 & it==0)

. 
. **** Making CapMkt more general
. 
. replace capmkt=1 if (consfin==1 | insur==1)
(1,813 real changes made)

. replace it=1 if otherind==1
(7,776 real changes made)

. 
. **** Weighted measures
. 
. gen bankwt=weighted_cite*bank
(3 missing values generated)

. gen bankkogan=kogan_etal_val* bank 
(14,756 missing values generated)

. egen csapatcount_bank=sum(bank), by(csa_code app_year)  

. egen csawtpatcount_bank=sum(bankwt), by(csa_code app_year)

. egen csakoganpatcount_bank=sum(bankkogan), by(csa_code app_year)

. drop bankwt bankkogan

. 
. gen capmktwt=weighted_cite*capmkt
(3 missing values generated)

. gen capmktkogan=kogan_etal_val* capmkt 
(14,756 missing values generated)

. egen csapatcount_capmkt=sum(capmkt), by(csa_code app_year)      

. egen csawtpatcount_capmkt=sum(capmktwt), by(csa_code app_year)

. egen csakoganpatcount_capmkt=sum(capmktkogan), by(csa_code app_year)

. drop capmktwt capmktkogan

. 
. gen paywt=weighted_cite*pay
(3 missing values generated)

. gen paykogan=kogan_etal_val*pay 
(14,756 missing values generated)

. egen csapatcount_pay=sum(pay), by(csa_code app_year)    

. egen csawtpatcount_pay=sum(paywt), by(csa_code app_year)

. egen csakoganpatcount_pay=sum(paykogan), by(csa_code app_year)

. drop paywt paykogan

. 
. gen itwt=weighted_cite*it
(3 missing values generated)

. gen itkogan=kogan_etal_val* it 
(14,756 missing values generated)

. egen csapatcount_it=sum(it), by(csa_code app_year)      

. egen csawtpatcount_it=sum(itwt), by(csa_code app_year)

. egen csakoganpatcount_it=sum(itkogan), by(csa_code app_year)

. drop itwt itkogan

. 
. *** Keeping what's left
. 
. by csa_code app_year: drop if _n~=1
(23,186 observations deleted)

. keep csa_code app_year csapatcount csawtpatcount csakoganpatcount csapatcount csawtpatcount csakoganpatcount ///
> csapatcount_small csawtpatcount_small csakoganpatcount_small csapatcount_medium csawtpatcount_medium csakoganpatcount_
> medium ///
> csapatcount_large csawtpatcount_large csakoganpatcount_large csapatcount_sifi csawtpatcount_sifi csakoganpatcount_sifi
>  ///
> csapatcount_nonsifi csawtpatcount_nonsifi csakoganpatcount_nonsifi csapatcount_payments csawtpatcount_payments csakoga
> npatcount_payments ///
> csapatcount_banking csawtpatcount_banking csakoganpatcount_banking csapatcount_other csawtpatcount_other csakoganpatco
> unt_other ///
> csapatcount_bank csawtpatcount_bank csakoganpatcount_bank csapatcount_capmkt csawtpatcount_capmkt csakoganpatcount_cap
> mkt ///
> csapatcount_pay csawtpatcount_pay csakoganpatcount_pay csapatcount_it csawtpatcount_it csakoganpatcount_it 

. save bridge, replace
file bridge.dta saved

. 
. ** Bridging in the variables
. 
. use csa_year_data_temp

. merge m:1 csa_code app_year using bridge

    Result                      Number of obs
    -----------------------------------------
    Not matched                         2,127
        from master                     2,106  (_merge==1)
        from using                         21  (_merge==2)

    Matched                             1,048  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(21 observations deleted)

. drop _merge

. foreach v of varlist csapatcount-csakoganpatcount_it {
  2.    replace `v' = 0 if `v' ==.
  3. }
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)
(2,106 real changes made)

. sum

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    app_year |      3,154        2009    5.478094       2000       2018
    csa_code |      3,154     336.747    127.2214        104        566
   csa_title |          0
  population |      3,154     1359217     2701148      32874   2.39e+07
  households |      3,154    501794.8    951437.5      12936    8516016
-------------+---------------------------------------------------------
median_hh_~e |      3,154    46408.88    8996.115    24062.7      96998
establishm~s |      3,154    2119.396      4038.8         74      35103
   employees |      2,964    32409.95     73348.1        301     719385
adult_popu~n |      3,154    898963.5     1797377      21671   1.66e+07
adult_pop_~s |      3,154    273499.4    619055.4       6225    6513532
-------------+---------------------------------------------------------
   n_patents |      3,154    4.938174    20.88896          0        334
weighted_c~e |      3,154    6.854281    34.60355          0   772.2792
kogan_etal~l |      3,154    6.015592    110.1475          0   4520.604
kelly_eta~10 |      3,154    2.340772    14.35535          0    515.541
kelly_etal~5 |      3,154     1.33668    7.169167          0   230.8097
-------------+---------------------------------------------------------
  accounting |      3,154    .2068106    .9695718          0     17.075
investment~g |      3,154    .4420139    2.844289          0   54.75952
commercial~g |      3,154     .248731    1.245391          0   22.17024
communica~ns |      3,154    .6441865    2.908105          0   55.56667
    payments |      3,154    1.869989      8.1518          0   144.8083
-------------+---------------------------------------------------------
cryptocurr~y |      3,154    .0583556     .352161          0   6.366667
    currency |      3,154    .0299584     .235473          0   4.058333
   insurance |      3,154    .0693453    .4575576          0      15.75
 real_estate |      3,154     .079876    .4688196          0          9
retail_ban~g |      3,154    .2971952    1.141312          0   14.85833
-------------+---------------------------------------------------------
    security |      3,154    .9158146    4.078045          0   78.18333
wealth_man~t |      3,154    .0758976    .4581148          0      8.125
communica~ts |      3,154    .1949905    1.300794          0         30
consumer_d~s |      3,154    .2247939    1.613221          0         38
consumer_s~s |      3,154    .0168041    .4146498          0         22
-------------+---------------------------------------------------------
energy_n_p~s |      3,154    .0041218    .0688504          0          2
financials~s |      3,154    1.154407    6.585932          0        117
health_car~s |      3,154    .0266328    .2265048          0          5
industrial~s |      3,154    .1360178    .7833197          0         18
informatio~s |      3,154    1.990805    10.24292          0        198
-------------+---------------------------------------------------------
materials_~s |      3,154    .0028535    .0589966          0          2
real_estat~s |      3,154    .0028535    .0641476          0          2
utilities_~s |      3,154    .0006341    .0251777          0          1
communicat~_ |      3,154    .4737828    4.723018          0   117.9068
consumer_d~_ |      3,154    .2706604    2.235952          0   57.49337
-------------+---------------------------------------------------------
consumer_s~e |      3,154    .0154525    .2901655          0   9.570528
energy_wei~e |      3,154     .003928    .1135119          0   4.799296
financials~e |      3,154    1.394783    15.57785          0   772.2792
health_car~e |      3,154    .0895124    1.667276          0   54.69445
industrial~e |      3,154    .1979254    1.636806          0   55.72709
-------------+---------------------------------------------------------
informatio~_ |      3,154    2.998554    19.14212          0   436.2282
materials_~e |      3,154    .0009703    .0346186          0   1.754635
real_est~ite |      3,154    .0039339    .1464156          0   7.911224
utilities_~e |      3,154    .0000775    .0043549          0   .2445759
banks_n_pa~s |      3,154    .3912492    2.675682          0         72
-------------+---------------------------------------------------------
capital_ma~s |      3,154    .4112238    3.632397          0         72
consumer_f~s |      3,154    .1081167    1.050596          0         27
diversifie~n |      3,154    .0279011    .2590235          0          7
insurance_~s |      3,154    .1724794     1.43869          0         54
thrifts_mo~n |      3,154    .0434369    .6309114          0         15
-------------+---------------------------------------------------------
banks_weig~e |      3,154    .4129839    3.022714          0   64.96134
capital_ma~e |      3,154    .1583929    1.377728          0   35.10248
consumer_f~e |      3,154    .1205234    1.318011          0   40.06008
diversifie~w |      3,154     .041833    .7943231          0    31.1338
insurance_~e |      3,154    .6318152    14.81007          0   772.2792
-------------+---------------------------------------------------------
thrifts_mo~e |      3,154    .0292349    .5355085          0    20.9901
vc_num_deals |      3,154     28.2397     133.444          0       2306
vc_sum_equ~d |      3,154    292.5022    1907.944          0   55689.49
us_ai_rank~g |        114         3.5    1.715365          1          6
    empshare |      3,154    .0263167     .017964          0   .4038696
-------------+---------------------------------------------------------
collegeshare |      3,154    .2532762    .0703293   .1110065   .5080002
       state |          0
    division |          0
Sum2000FinVC |      3,154    20.23988    109.3956          0    1107.68
  app_period |      3,154    2007.105    5.457824       2000       2015
-------------+---------------------------------------------------------
 csapatcount |      3,154    4.938174    20.88896          0        334
csawtpatc~nt |      3,154    6.886415    34.64422          0   772.2792
csakoganp~nt |      3,154    125.3095     737.792          0   15699.61
csapatcoun~l |      3,154    .1030438    .7135832          0         14
csawtpatco~l |      3,154    .2027677    2.072134          0   44.60564
-------------+---------------------------------------------------------
csakoganpa~l |      3,154    .0683226    .7726501          0   24.75027
csapatcoun~m |      3,154    1.232086    6.889415          0        135
csawtpatco~m |      3,154    1.407552    10.67126          0   264.1156
csakoganpa~m |      3,154    26.48714    216.0691          0    6128.41
csapatcoun~e |      3,154    1.322765    6.667097          0        168
-------------+---------------------------------------------------------
csawtpatco~e |      3,154    1.992764    17.65018          0   772.2792
csakoganpa~e |      3,154     97.1657    631.8512          0   14662.03
csapat~_sifi |      3,154    .4156627    3.123632          0         72
csawtp~_sifi |      3,154    .3752843    2.948059          0   64.96134
csakog~_sifi |      3,154    67.39411    470.0247          0   9162.548
-------------+---------------------------------------------------------
csapat~nsifi |      3,154    4.522511     19.4658          0        327
csawtp~nsifi |      3,154    6.511131    33.79754          0   772.2792
csakog~nsifi |      3,154    57.91538    421.4074          0   13781.61
csapatcoun~s |      3,154    1.869989      8.1518          0   144.8083
csawtpatco~s |      3,154    2.613582    13.99704          0   288.2928
-------------+---------------------------------------------------------
csakoganpa~s |      3,154    53.62884    323.0073          0   7452.102
csapatcoun~g |      3,154    .4277108     2.44962          0         46
csawtpatco~g |      3,154    .4661224    3.247108          0    84.2317
csakoganpa~g |      3,154    9.104609    67.82444          0   1263.834
csapatcoun~r |      3,154    3.448003    14.56804          0        248
-------------+---------------------------------------------------------
csawtpatco~r |      3,154    4.958123    26.09782          0   673.4524
csakoganpa~r |      3,154    85.88987    524.3921          0   12236.03
csapatcoun~k |      3,154    .4346861    2.772311          0         72
csawtpatco~k |      3,154    .4422188    3.088882          0   64.96134
csakoganpa~k |      3,154    56.97635    360.7738          0   6328.096
-------------+---------------------------------------------------------
csapatcou~kt |      3,154    .7108434    5.075712          0         96
csawtpatc~kt |      3,154    .9517909    15.11112          0   772.2792
csakoganp~kt |      3,154    26.06288     298.631          0     9512.3
csapatcoun~y |      3,154     .593532    5.034638          0        128
csawtpatco~y |      3,154    .9421711    10.85048          0   295.6935
-------------+---------------------------------------------------------
csakoganpa~y |      3,154    21.94749    235.2716          0   5296.499
csapatcou~it |      3,154    3.199112     12.9759          0        226
csawtpatc~it |      3,154    4.550234    20.76779          0   376.0438
csakoganp~it |      3,154    20.32278    186.1448          0   8293.574

. save csa_year_data_temp, replace
file csa_year_data_temp.dta saved

. 
. * Analysis--Table 8
. 
. ** Top 10 CSAs listing
. 
. egen csapattotal=sum(csapatcount), by(csa_code)

. by csa_code, sort: drop if _n~=1
(2,988 observations deleted)

. sort csapattotal

. list csa_title csa_code csapattotal in -10/l

     +------------------------------------------------------------------------+
     | csa_title                                          csa_code   csapa~al |
     |------------------------------------------------------------------------|
157. | Charlotte-Concord, NC-SC                                172        451 |
158. | Denver-Aurora, CO                                       216        488 |
159. | Seattle-Tacoma, WA                                      500        541 |
160. | Atlanta--Athens-Clarke County--Sandy Springs, GA        122        550 |
161. | Los Angeles-Long Beach, CA                              348        577 |
     |------------------------------------------------------------------------|
162. | Cleveland-Akron-Canton, OH                              184        619 |
163. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA          548        859 |
164. | Chicago-Naperville, IL-IN-WI                            176       1404 |
165. | New York-Newark, NY-NJ-CT-PA                            408       2580 |
166. | San Jose-San Francisco-Oakland, CA                      488       3107 |
     +------------------------------------------------------------------------+

. use csa_year_data_temp, clear

. 
. ** Computing 5-year totals for each CSA
. 
. *** Totals
. 
. egen csapatperiod=sum(csapatcount), by(csa_code app_period)

. egen csapatperiod_small=sum(csapatcount_small), by(csa_code app_period)

. egen csapatperiod_medium=sum(csapatcount_medium), by(csa_code app_period)

. egen csapatperiod_large=sum(csapatcount_large), by(csa_code app_period)

. egen csapatperiod_sifi=sum(csapatcount_sifi), by(csa_code app_period)

. egen csapatperiod_payments=sum(csapatcount_payments), by(csa_code app_period)

. egen csapatperiod_banking=sum(csapatcount_banking), by(csa_code app_period)

. egen csapatperiod_other=sum(csapatcount_other), by(csa_code app_period)

. egen csapatperiod_bank=sum(csapatcount_bank), by(csa_code app_period)

. egen csapatperiod_capmkt=sum(csapatcount_capmkt), by(csa_code app_period)

. egen csapatperiod_pay=sum(csapatcount_pay), by(csa_code app_period)

. egen csapatperiod_it=sum(csapatcount_it), by(csa_code app_period)

. 
. egen csawtpatperiod=sum(csawtpatcount), by(csa_code app_period)

. egen csawtpatperiod_small=sum(csawtpatcount_small), by(csa_code app_period)

. egen csawtpatperiod_medium=sum(csawtpatcount_medium), by(csa_code app_period)

. egen csawtpatperiod_large=sum(csawtpatcount_large), by(csa_code app_period)

. egen csawtpatperiod_sifi=sum(csawtpatcount_sifi), by(csa_code app_period)

. egen csawtpatperiod_payments=sum(csawtpatcount_payments), by(csa_code app_period)

. egen csawtpatperiod_banking=sum(csawtpatcount_banking), by(csa_code app_period)

. egen csawtpatperiod_other=sum(csawtpatcount_other), by(csa_code app_period)

. egen csawtpatperiod_bank=sum(csawtpatcount_bank), by(csa_code app_period)

. egen csawtpatperiod_capmkt=sum(csawtpatcount_capmkt), by(csa_code app_period)

. egen csawtpatperiod_pay=sum(csawtpatcount_pay), by(csa_code app_period)

. egen csawtpatperiod_it=sum(csawtpatcount_it), by(csa_code app_period)

. 
. egen csakoganpatperiod=sum(csakoganpatcount), by(csa_code app_period)

. egen csakoganpatperiod_small=sum(csakoganpatcount_small), by(csa_code app_period)

. egen csakoganpatperiod_medium=sum(csakoganpatcount_medium), by(csa_code app_period)

. egen csakoganpatperiod_large=sum(csakoganpatcount_large), by(csa_code app_period)

. egen csakoganpatperiod_sifi=sum(csakoganpatcount_sifi), by(csa_code app_period)

. egen csakoganpatperiod_payments=sum(csakoganpatcount_payments), by(csa_code app_period)

. egen csakoganpatperiod_banking=sum(csakoganpatcount_banking), by(csa_code app_period)

. egen csakoganpatperiod_other=sum(csakoganpatcount_other), by(csa_code app_period)

. egen csakoganpatperiod_bank=sum(csakoganpatcount_bank), by(csa_code app_period)

. egen csakoganpatperiod_capmkt=sum(csakoganpatcount_capmkt), by(csa_code app_period)

. egen csakoganpatperiod_pay=sum(csakoganpatcount_pay), by(csa_code app_period)

. egen csakoganpatperiod_it=sum(csakoganpatcount_it), by(csa_code app_period)

. 
. ***  Normalizing
. 
. foreach v of varlist csapatperiod-csapatperiod_it {
  2.    replace `v' = `v'/5317 if app_period==2000
  3.    replace `v' = `v'/7564 if app_period==2005
  4.    replace `v' = `v'/8881 if app_period==2010
  5.    replace `v' = `v'/2493 if app_period==2015
  6.   }
(460 real changes made)
(490 real changes made)
(465 real changes made)
(252 real changes made)
(100 real changes made)
(90 real changes made)
(70 real changes made)
(28 real changes made)
(220 real changes made)
(260 real changes made)
(215 real changes made)
(96 real changes made)
(255 real changes made)
(285 real changes made)
(260 real changes made)
(132 real changes made)
(105 real changes made)
(155 real changes made)
(140 real changes made)
(76 real changes made)
(400 real changes made)
(450 real changes made)
(415 real changes made)
(212 real changes made)
(210 real changes made)
(185 real changes made)
(210 real changes made)
(92 real changes made)
(425 real changes made)
(450 real changes made)
(435 real changes made)
(224 real changes made)
(150 real changes made)
(185 real changes made)
(180 real changes made)
(80 real changes made)
(140 real changes made)
(170 real changes made)
(185 real changes made)
(64 real changes made)
(105 real changes made)
(160 real changes made)
(155 real changes made)
(84 real changes made)
(450 real changes made)
(475 real changes made)
(435 real changes made)
(224 real changes made)

. 
. foreach v of varlist csawtpatperiod-csawtpatperiod_it {
  2.    replace `v' = `v'/6264.2 if app_period==2000
  3.    replace `v' = `v'/8682.2 if app_period==2005
  4.    replace `v' = `v'/11468.6 if app_period==2010
  5.    replace `v' = `v'/3880.8 if app_period==2015
  6.   }
(445 real changes made)
(435 real changes made)
(410 real changes made)
(164 real changes made)
(95 real changes made)
(80 real changes made)
(55 real changes made)
(16 real changes made)
(210 real changes made)
(250 real changes made)
(180 real changes made)
(64 real changes made)
(255 real changes made)
(265 real changes made)
(215 real changes made)
(72 real changes made)
(105 real changes made)
(140 real changes made)
(120 real changes made)
(24 real changes made)
(390 real changes made)
(390 real changes made)
(360 real changes made)
(124 real changes made)
(200 real changes made)
(155 real changes made)
(155 real changes made)
(36 real changes made)
(410 real changes made)
(410 real changes made)
(370 real changes made)
(156 real changes made)
(150 real changes made)
(175 real changes made)
(150 real changes made)
(24 real changes made)
(140 real changes made)
(155 real changes made)
(140 real changes made)
(36 real changes made)
(105 real changes made)
(140 real changes made)
(130 real changes made)
(40 real changes made)
(435 real changes made)
(420 real changes made)
(360 real changes made)
(132 real changes made)

. 
. foreach v of varlist csakoganpatperiod-csakoganpatperiod_it {
  2.    replace `v' = `v'/121813 if app_period==2000
  3.    replace `v' = `v'/160676 if app_period==2005
  4.    replace `v' = `v'/174532 if app_period==2010
  5.    replace `v' = `v'/52200 if app_period==2015
  6.   }
(310 real changes made)
(310 real changes made)
(290 real changes made)
(128 real changes made)
(55 real changes made)
(30 real changes made)
(40 real changes made)
(8 real changes made)
(195 real changes made)
(195 real changes made)
(190 real changes made)
(52 real changes made)
(245 real changes made)
(265 real changes made)
(220 real changes made)
(112 real changes made)
(105 real changes made)
(150 real changes made)
(135 real changes made)
(72 real changes made)
(280 real changes made)
(260 real changes made)
(250 real changes made)
(104 real changes made)
(120 real changes made)
(110 real changes made)
(115 real changes made)
(40 real changes made)
(285 real changes made)
(290 real changes made)
(255 real changes made)
(108 real changes made)
(120 real changes made)
(150 real changes made)
(150 real changes made)
(76 real changes made)
(105 real changes made)
(115 real changes made)
(95 real changes made)
(36 real changes made)
(85 real changes made)
(90 real changes made)
(90 real changes made)
(48 real changes made)
(260 real changes made)
(280 real changes made)
(210 real changes made)
(76 real changes made)

. 
. by csa_code app_period, sort: drop if _n~=1
(2,490 observations deleted)

. 
. gen csapatperiod_bc=csapatperiod_bank+csapatperiod_capmkt

. gen csapatperiod_pi=csapatperiod_pay+csapatperiod_it

. 
. 
. 
. save csa_year_data_temp2, replace
file csa_year_data_temp2.dta saved

. 
. ** Overall tabulation
. 
. foreach v of varlist csapatperiod-csakoganpatperiod_it {
  2.    replace `v' = `v'*166
  3.   }
(346 real changes made)
(59 real changes made)
(163 real changes made)
(193 real changes made)
(99 real changes made)
(306 real changes made)
(144 real changes made)
(318 real changes made)
(123 real changes made)
(115 real changes made)
(105 real changes made)
(328 real changes made)
(299 real changes made)
(50 real changes made)
(144 real changes made)
(165 real changes made)
(79 real changes made)
(259 real changes made)
(111 real changes made)
(277 real changes made)
(101 real changes made)
(96 real changes made)
(85 real changes made)
(276 real changes made)
(214 real changes made)
(27 real changes made)
(129 real changes made)
(174 real changes made)
(96 real changes made)
(184 real changes made)
(79 real changes made)
(193 real changes made)
(103 real changes made)
(72 real changes made)
(65 real changes made)
(169 real changes made)

. by app_period, sort: sum csapatperiod-csakoganpatperiod_it

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |        166     .599022    2.242299          0    22.2603
csapatperi~l |        166     .022193    .1111182          0    1.03028
csapatperi~m |        166    .1545985    .6141751          0   4.683092
csapatperi~e |        166    .1406808    .6443564          0   7.461727
csapatper~fi |        166    .0410006    .3429164          0   4.308444
-------------+---------------------------------------------------------
csapatperi~s |        166    .2090397    .7684423          0   7.449659
csapatperi~g |        166    .0530374    .2336961          0   2.622531
csapatperi~r |        166    .4338913    1.629264          0   15.89129
csapatperi~k |        166    .0368629    .1909867          0   1.685913
csapatper~kt |        166    .0838819    .6195194          0   7.805153
-------------+---------------------------------------------------------
csapatperi~y |        166    .0492759    .2533168          0   2.684973
csapatper~it |        166    .4290013    1.471166          0   11.86383
csawtpatpe~d |        166    .6864749    2.659109          0   24.27024
csawtpatpe~l |        166    .0388874    .2730158          0   3.159261
csawtpatpe~m |        166    .1544006    .6181972          0   5.458261
-------------+---------------------------------------------------------
csawtpatpe~e |        166    .1404462    .6807391          0   7.722418
csawtpatpe~i |        166    .0457327    .3252309          0   3.852996
csawtpatpe~s |        166    .2474605     .980244          0   9.184997
csawtpatpe~g |        166    .0511726     .205447          0   1.920599
csawtpatpe~r |        166    .5057446    1.982399          0   17.73866
-------------+---------------------------------------------------------
csawtpatpe~k |        166    .0520733    .2907644          0   2.982068
csawtpatp~kt |        166    .0682073    .4886991          0   6.126788
csawtpatpe~y |        166    .0569691    .2991254          0    2.49266
csawtpatp~it |        166    .5092251    1.860619          0   15.04811
csakoganpa~d |        166    .7834522    4.739149          0   57.49314
-------------+---------------------------------------------------------
csak~d_small |        166    .0009234     .005873          0   .0519792
csakoganpa.. |        166    .1544554     .664262          0   5.012898
csak~d_large |        166    .6208355    4.334627          0   53.61988
csako~d_sifi |        166    .4775724    3.716409          0   45.76853
csakoganpa.. |        166    .3092304     1.80251          0   20.25163
-------------+---------------------------------------------------------
csakoganpa.. |        166    .0617714    .4961572          0    6.27591
csak~d_other |        166    .5509829    3.325299          0   40.51495
csako~d_bank |        166    .3308371    1.884692          0   18.95094
csakoganpa.. |        166    .2751529    2.768239          0   35.56047
csakog~d_pay |        166    .0555564    .3712664          0   4.243984
-------------+---------------------------------------------------------
csakoga~d_it |        166    .1219059    .5840521          0   6.605674

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |        166    .6311475    2.316538          0   19.26864
csapatperi~l |        166    .0128239    .0690267          0   .6583818
csapatperi~m |        166    .1759651    .8173821          0   8.405341
csapatperi~e |        166    .1544157    .6121285          0   5.947382
csapatper~fi |        166    .0557906    .3271193          0   3.094394
-------------+---------------------------------------------------------
csapatperi~s |        166    .2412542    .8806831          0   7.138217
csapatperi~g |        166    .0597567    .2800961          0   2.523797
csapatperi~r |        166    .4335008    1.566417          0   13.05791
csapatperi~k |        166    .0594923    .2749574          0   2.501851
csapatper~kt |        166    .0965098    .6283182          0   7.395822
-------------+---------------------------------------------------------
csapatperi~y |        166    .0610788    .3601254          0   3.950291
csapatper~it |        166    .4140666    1.468626          0   12.72871
csawtpatpe~d |        166    .6930558     2.65515          0   26.92303
csawtpatpe~l |        166    .0216549    .1670956          0   1.938393
csawtpatpe~m |        166    .1484664     .920561          0   11.28804
-------------+---------------------------------------------------------
csawtpatpe~e |        166     .158951     .549757          0   3.755669
csawtpatpe~i |        166    .0427756    .2276455          0   2.291606
csawtpatpe~s |        166    .2931576    1.177048          0   12.34087
csawtpatpe~g |        166    .0417616    .2026412          0   1.814624
csawtpatpe~r |        166    .4809636    1.822714          0   18.68498
-------------+---------------------------------------------------------
csawtpatpe~k |        166    .0543119    .2448368          0   2.291606
csawtpatp~kt |        166    .0479123    .2491132          0   2.691863
csawtpatpe~y |        166    .0725201    .5785693          0   7.283388
csawtpatp~it |        166    .5183115    1.939804          0   18.71297
csakoganpa~d |        166    .7919493    3.672439          0   32.81142
-------------+---------------------------------------------------------
csak~d_small |        166    .0004083    .0026565          0   .0286358
csakoganpa.. |        166    .1946468     1.45867          0   17.92369
csak~d_large |        166    .5913311    2.899025          0   28.56647
csako~d_sifi |        166     .478374    2.604526          0   24.38117
csakoganpa.. |        166    .3553995    1.614689          0   11.33545
-------------+---------------------------------------------------------
csakoganpa.. |        166    .0616946    .3582531          0   4.109874
csak~d_other |        166    .5197293    2.475993          0   23.09488
csako~d_bank |        166    .4086499    2.050702          0   18.18579
csakoganpa.. |        166    .1576521    1.371832          0   17.21908
csakog~d_pay |        166    .1079988    1.027191          0   13.03729
-------------+---------------------------------------------------------
csakoga~d_it |        166    .1176485    .6300494          0   6.947103

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |        166    .6746988    2.661165          0   26.03738
csapatperi~l |        166    .0110348    .0543713          0   .3925234
csapatperi~m |        166    .1587659     .820114          0   8.953271
csapatperi~e |        166    .1875915    .8167537          0   8.093458
csapatper~fi |        166    .0560748    .3263535          0   3.364486
-------------+---------------------------------------------------------
csapatperi~s |        166    .2670458    1.056705          0   11.03853
csapatperi~g |        166    .0581016    .3057455          0   3.327103
csapatperi~r |        166    .4621101    1.863627          0    19.1215
csapatperi~k |        166    .0611418    .3045615          0   3.364486
csapatper~kt |        166    .0969485    .5316917          0   5.308411
-------------+---------------------------------------------------------
csapatperi~y |        166    .0883909     .674605          0   8.504673
csapatper~it |        166    .4282175    1.631363          0   15.85047
csawtpatpe~d |        166    .7480923    3.167875          0   35.32751
csawtpatpe~l |        166    .0171919    .0925237          0   .7676751
csawtpatpe~m |        166     .145472    .9664981          0   11.95479
-------------+---------------------------------------------------------
csawtpatpe~e |        166     .238055    1.152513          0    12.1099
csawtpatpe~i |        166      .03767    .2287048          0   2.732907
csawtpatpe~s |        166    .2816983    1.332438          0   15.84951
csawtpatpe~g |        166    .0486275    .2197771          0   1.627766
csawtpatpe~r |        166    .5379939     2.31459          0    25.9801
-------------+---------------------------------------------------------
csawtpatpe~k |        166    .0432162     .234675          0   2.732907
csawtpatp~kt |        166    .1002184     .580877          0   6.098641
csawtpatpe~y |        166    .1241184    1.159613          0   14.85439
csawtpatp~it |        166    .4805394    1.853094          0   19.13752
csakoganpa~d |        166    .7654596    3.972226          0   41.44814
-------------+---------------------------------------------------------
csak~d_small |        166    .0001765    .0009529          0   .0089456
csakoganpa.. |        166    .1530985    .9142766          0   9.667863
csak~d_large |        166    .6009531    3.125803          0   31.59244
csako~d_sifi |        166    .3453418    1.747346          0   13.77523
csakoganpa.. |        166    .3351431    1.720517          0   17.90033
-------------+---------------------------------------------------------
csakoganpa.. |        166    .0509036    .2476849          0   2.102865
csak~d_other |        166    .5370393    2.932521          0   31.41533
csako~d_bank |        166    .3226927    1.546948          0   13.51072
csakoganpa.. |        166    .1140516     .876165          0   9.865483
csakog~d_pay |        166    .1763203    1.490012          0   18.55998
-------------+---------------------------------------------------------
csakoga~d_it |        166    .1523949     1.18278          0   14.79131

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |        166     .651424    2.687853          0   30.29683
csapatperi~l |        166    .0048135    .0259873          0   .1997593
csapatperi~m |        166    .1295628    .8456106          0   10.45407
csapatperi~e |        166    .2366627    1.019935          0    8.98917
csapatper~fi |        166    .0693943    .5026018          0   6.325712
-------------+---------------------------------------------------------
csapatperi~s |        166    .2366631    1.098466          0   12.93442
csapatperi~g |        166    .0397112    .1480736          0   1.198556
csapatperi~r |        166    .4753309    1.931249          0   21.64059
csapatperi~k |        166    .0730044    .5055272          0   6.325712
csapatper~kt |        166    .0822302    .5018295          0   5.460088
-------------+---------------------------------------------------------
csapatperi~y |        166    .1456077    1.221025          0   15.44805
csapatper~it |        166    .3505816    1.313447          0   13.65022
csawtpatpe~d |        166    .7273545    4.207689          0   39.16488
csawtpatpe~l |        166    .0027706    .0191504          0   .1955557
csawtpatpe~m |        166    .1326657    1.247693          0   15.94551
-------------+---------------------------------------------------------
csawtpatpe~e |        166    .3337437    3.086219          0   39.16488
csawtpatpe~i |        166    .0241596     .204573          0   2.525529
csawtpatpe~s |        166    .2363322    1.460367          0   15.87654
csawtpatpe~g |        166    .0590913    .4365814          0   5.177569
csawtpatpe~r |        166    .5473035    3.234476          0   31.80813
-------------+---------------------------------------------------------
csawtpatpe~k |        166    .0261247    .2088584          0   2.525529
csawtpatp~kt |        166    .2600844    3.044448          0   39.16488
csawtpatpe~y |        166    .1447237    1.446287          0   18.44512
csawtpatp~it |        166    .2964218    1.527551          0   16.64829
csakoganpa~d |        166    .7461119    3.926726          0   42.55407
-------------+---------------------------------------------------------
csak~d_small |        166    .0001265    .0014053          0   .0178506
csakoganpa.. |        166    .1289293    .8652856          0   8.999713
csak~d_large |        166    .5926531    3.136153          0   32.10799
csako~d_sifi |        166    .3304617    1.865254          0   21.69218
csakoganpa.. |        166    .3042088    1.820412          0   21.21144
-------------+---------------------------------------------------------
csakoganpa.. |        166    .0458664    .2340825          0   2.034112
csak~d_other |        166    .5084522    2.620664          0   27.08632
csako~d_bank |        166    .3337682    1.868048          0   21.69218
csakoganpa.. |        166    .0660645    .5207721          0   6.279686
csakog~d_pay |        166    .2744929     2.37335          0   29.42031
-------------+---------------------------------------------------------
csakoga~d_it |        166    .0717862    .4449401          0   4.812548


. foreach v of varlist csapatperiod-csakoganpatperiod_it {
  2.    replace `v' = `v'/166
  3.   }
(346 real changes made)
(59 real changes made)
(163 real changes made)
(193 real changes made)
(99 real changes made)
(306 real changes made)
(144 real changes made)
(318 real changes made)
(123 real changes made)
(115 real changes made)
(105 real changes made)
(328 real changes made)
(299 real changes made)
(50 real changes made)
(144 real changes made)
(165 real changes made)
(79 real changes made)
(259 real changes made)
(111 real changes made)
(277 real changes made)
(101 real changes made)
(96 real changes made)
(85 real changes made)
(276 real changes made)
(214 real changes made)
(27 real changes made)
(129 real changes made)
(174 real changes made)
(96 real changes made)
(184 real changes made)
(79 real changes made)
(193 real changes made)
(103 real changes made)
(72 real changes made)
(65 real changes made)
(169 real changes made)

. 
. save before_merge_non_csa_data, replace 
file before_merge_non_csa_data.dta saved

.  
. clear

. use financial_patent_data_v3

. sort csa_code app_year

. 
. ** Drop any non us patents
. 
. keep if inventor_1_country=="US"
(5,103 observations deleted)

. drop state_fips

. 
. ** Map them to different Census region, remove non-matched patents.
. 
. merge m:1 state using temp, keepusing(division)

    Result                      Number of obs
    -----------------------------------------
    Not matched                             4
        from master                         4  (_merge==1)
        from using                          0  (_merge==2)

    Matched                            19,148  (_merge==3)
    -----------------------------------------

. drop if _merge==1
(4 observations deleted)

. drop if _merge==2
(0 observations deleted)

. drop _merge

. 
. ** Create app_period
. 
. gen app_period=2000 if app_year>=2000 & app_year<=2004
(15,260 missing values generated)

. replace app_period=2005 if app_year>=2005 & app_year<=2009
(6,054 real changes made)

. replace app_period=2010 if app_year>=2010 & app_year<=2014
(7,262 real changes made)

. replace app_period=2015 if app_year>=2015 & app_year<=2019
(1,944 real changes made)

. drop if app_period==.
(0 observations deleted)

. 
. *** Total patents
. 
. egen statepatcount=count(patent_id), by(state app_year)

. egen statewtpatcount=sum(weighted_cite), by(state app_year)

. egen statekoganpatcount=sum(kogan_etal_val), by(state app_year)

. 
. by state app_year, sort: drop if _n~=1
(18,384 observations deleted)

. 
. egen statepatperiod=sum(statepatcount), by(state app_period)

. egen statewtpatperiod=sum(statewtpatcount), by(state app_period)

. egen statekoganpatperiod=sum(statekoganpatcount), by(state app_period)

. 
. ***  Normalizing
. 
. foreach v of varlist statepatperiod {
  2.    replace `v' = `v'/5317 if app_period==2000
  3.    replace `v' = `v'/7564 if app_period==2005
  4.    replace `v' = `v'/8881 if app_period==2010
  5.    replace `v' = `v'/2493 if app_period==2015
  6.   }
(206 real changes made)
(212 real changes made)
(217 real changes made)
(129 real changes made)

. 
. foreach v of varlist statewtpatperiod {
  2.    replace `v' = `v'/6264.2 if app_period==2000
  3.    replace `v' = `v'/8682.2 if app_period==2005
  4.    replace `v' = `v'/11468.6 if app_period==2010
  5.    replace `v' = `v'/3880.8 if app_period==2015
  6.   }
(206 real changes made)
(209 real changes made)
(214 real changes made)
(116 real changes made)

. 
. foreach v of varlist statekoganpatperiod{
  2.    replace `v' = `v'/121813 if app_period==2000
  3.    replace `v' = `v'/160676 if app_period==2005
  4.    replace `v' = `v'/174532 if app_period==2010
  5.    replace `v' = `v'/52200 if app_period==2015
  6.   }
(194 real changes made)
(194 real changes made)
(196 real changes made)
(104 real changes made)

. 
. by state app_period, sort: drop if _n~=1
(575 observations deleted)

. 
. ** updated Table A21 for each Census region based on each patent rather than state information.
. 
. by division, sort: sum statepatperiod statewtpatperiod statekoganpatperiod

------------------------------------------------------------------------------------------------------------------------
-> division = East North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         20    .0215218    .0259131   .0020056   .0851256
statewtpat~d |         20    .0299923    .0606495          0   .2603088
statekogan~d |         20     .011942    .0168989          0   .0474407

------------------------------------------------------------------------------------------------------------------------
-> division = East South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         15    .0012519    .0010275   .0001126   .0037017
statewtpat~d |         15    .0009687    .0013793          0   .0052099
statekogan~d |         15    .0006194    .0009294          0   .0033947

------------------------------------------------------------------------------------------------------------------------
-> division = Middle Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         12    .0413044    .0290108   .0068191   .0942261
statewtpat~d |         12    .0431633    .0332191    .012477    .111233
statekogan~d |         12    .0798464    .0690774   .0090807    .256399

------------------------------------------------------------------------------------------------------------------------
-> division = Mountain

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         27    .0082556    .0077685   .0002252   .0252022
statewtpat~d |         27    .0074241     .007523          0   .0246082
statekogan~d |         27      .00654    .0090156          0    .028469

------------------------------------------------------------------------------------------------------------------------
-> division = New England

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         22    .0101621    .0122623   .0002644   .0332894
statewtpat~d |         22    .0079406    .0107193          0     .03109
statekogan~d |         22    .0063091    .0103111          0   .0354541

------------------------------------------------------------------------------------------------------------------------
-> division = Pacific

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         19    .0464774    .0771197   .0001126   .2362615
statewtpat~d |         19    .0615875    .1057579          0   .3067726
statekogan~d |         19    .0508151    .0945459          0   .2934223

------------------------------------------------------------------------------------------------------------------------
-> division = South Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         33    .0153198    .0106741   .0001126   .0381067
statewtpat~d |         33    .0139941    .0113766          0   .0395073
statekogan~d |         33     .023342    .0246342          0   .0999247

------------------------------------------------------------------------------------------------------------------------
-> division = West North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         26    .0052953    .0045421   .0002252   .0160449
statewtpat~d |         26    .0041691    .0041037          0   .0147262
statekogan~d |         26    .0075727    .0124496          0   .0557111

------------------------------------------------------------------------------------------------------------------------
-> division = West South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |         15    .0140972    .0227587   .0003378   .0635907
statewtpat~d |         15    .0183112    .0308789          0    .087479
statekogan~d |         15    .0120187    .0168426          0   .0576833


. by app_period division, sort: sum statepatperiod statewtpatperiod statekoganpatperiod

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = East North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5     .016325    .0158255   .0031973   .0362987
statewtpat~d |          5    .0184751    .0225962   .0021047   .0570775
statekogan~d |          5    .0094739    .0127874   3.08e-07   .0309275

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = East South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0014576     .001023   .0003762   .0028211
statewtpat~d |          4    .0011929     .000864   .0000723   .0021586
statekogan~d |          4    .0009588     .001626   .0000321   .0033947

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = Middle Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          3    .0521597    .0385791   .0184314   .0942261
statewtpat~d |          3    .0546377    .0495013   .0194036    .111233
statekogan~d |          3    .1412695    .1042151   .0533784    .256399

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = Mountain

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          6      .00978    .0087369   .0015046   .0252022
statewtpat~d |          6    .0124675    .0095679   .0005949   .0229209
statekogan~d |          6    .0104472    .0115392   .0004258    .028469

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = New England

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0127892    .0151258   .0009404   .0332894
statewtpat~d |          5    .0130522    .0135558   .0004985     .03109
statekogan~d |          5    .0093959    .0151542   .0000457   .0354541

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = Pacific

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0333647    .0566511   .0003762    .133534
statewtpat~d |          5     .044756    .0744131   .0000804   .1762074
statekogan~d |          5    .0226874    .0398578          0   .0923363

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = South Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          8    .0140587    .0097368   .0026331   .0299041
statewtpat~d |          8    .0156355    .0096466   .0024195   .0273685
statekogan~d |          8    .0188759    .0159554   .0007117   .0421456

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = West North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          6    .0052975    .0032367   .0003762   .0090276
statewtpat~d |          6    .0043112    .0024933   .0005443   .0066044
statekogan~d |          6    .0060659    .0036088          0   .0097836

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000, division = West South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0134004    .0250466   .0005642   .0509686
statewtpat~d |          4    .0140037    .0264114   .0000904   .0536034
statekogan~d |          4    .0144365    .0288312          0   .0576833

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = East North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0220783    .0266775   .0025119   .0629297
statewtpat~d |          5    .0184989    .0249673   .0010475   .0599637
statekogan~d |          5    .0137016    .0192352    .000564   .0458607

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = East South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0014212    .0015988   .0001322   .0037017
statewtpat~d |          4    .0014786    .0024927   .0000228   .0052099
statekogan~d |          4    .0005265    .0005576   .0000775   .0012627

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = Middle Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          3    .0496651    .0352585   .0224749   .0895029
statewtpat~d |          3    .0413593    .0324199   .0190743   .0785514
statekogan~d |          3    .0894236    .0522412   .0485398   .1482781

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = Mountain

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          7    .0084234    .0091214   .0002644   .0220783
statewtpat~d |          7    .0082319    .0090684          0   .0246082
statekogan~d |          7    .0079796    .0107762          0   .0276402

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = New England

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          6    .0091883    .0129133   .0002644   .0274987
statewtpat~d |          6    .0066926     .011077          0   .0274448
statekogan~d |          6    .0052677    .0096622          0   .0242982

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = Pacific

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0479574    .0729826   .0007932   .1561343
statewtpat~d |          4    .0685544    .1081807   .0001184   .2299994
statekogan~d |          4    .0475191    .0823107   .0006797   .1704104

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = South Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          8    .0154019    .0106533   .0017187   .0267054
statewtpat~d |          8    .0193065    .0157462   .0009734   .0395073
statekogan~d |          8    .0264167    .0318429   .0004051   .0999247

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = West North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          7    .0057226    .0053527    .000661   .0156002
statewtpat~d |          7    .0057846    .0043709   .0002787   .0115828
statekogan~d |          7    .0068423    .0109671          0   .0295673

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005, division = West South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0165256    .0313786   .0005288   .0635907
statewtpat~d |          4    .0224882    .0433278   .0006297    .087479
statekogan~d |          4    .0132824    .0162854          0   .0339136

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = East North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5     .025943    .0356662   .0020268   .0851256
statewtpat~d |          5    .0272061    .0455329   .0004334    .106436
statekogan~d |          5    .0123051    .0199818   .0004734   .0470808

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = East South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0010134    .0009331   .0001126   .0020268
statewtpat~d |          4    .0004451    .0003362          0   .0007254
statekogan~d |          4    .0006838    .0008059          0   .0015649

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = Middle Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          3    .0398604    .0271646   .0200428   .0708254
statewtpat~d |          3    .0457752    .0413606   .0213914   .0935307
statekogan~d |          3    .0642733    .0406376   .0376446    .111048

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = Mountain

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          8    .0064886    .0077725   .0002252   .0220696
statewtpat~d |          8    .0049429    .0051402   .0000207   .0129091
statekogan~d |          8    .0039307    .0057157          0   .0128537

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = New England

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          6    .0099276     .013305   .0003378   .0284878
statewtpat~d |          6    .0067347    .0099283   .0000269   .0223737
statekogan~d |          6    .0064425    .0111216   .0001687   .0277514

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = Pacific

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0510528     .093731   .0001126   .2177683
statewtpat~d |          5    .0692946    .1331657          0   .3067726
statekogan~d |          5    .0653218    .1256146          0   .2893892

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = South Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          9    .0130491    .0099058   .0001126   .0261232
statewtpat~d |          9    .0130862     .011133   .0000121   .0323086
statekogan~d |          9    .0187365    .0213359          0   .0699645

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = West North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          7    .0046488    .0043826   .0002252   .0119356
statewtpat~d |          7    .0045356    .0057686          0   .0147262
statekogan~d |          7    .0058303    .0098348          0   .0269237

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010, division = West South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          4    .0119074    .0217982   .0003378   .0445896
statewtpat~d |          4    .0137771    .0258085   .0000405   .0524513
statekogan~d |          4    .0071129    .0093521          0   .0197036

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = East North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0217409    .0299454   .0020056   .0734055
statewtpat~d |          5    .0557893    .1144226          0   .2603088
statekogan~d |          5    .0122875    .0202951          0   .0474407

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = East South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          3    .0010697    .0006127   .0004011   .0016045
statewtpat~d |          3     .000688    .0011917          0    .002064
statekogan~d |          3     .000205    .0003551          0    .000615

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = Middle Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          3    .0235326    .0200254   .0068191    .045728
statewtpat~d |          3    .0308808    .0204522    .012477   .0528994
statekogan~d |          3    .0244191    .0152986   .0090807   .0396775

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = Mountain

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          6    .0088916    .0066901   .0008022   .0180505
statewtpat~d |          6    .0047465    .0041464          0   .0117826
statekogan~d |          6    .0044322    .0081837          0   .0203369

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = New England

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0089852    .0109103   .0004011   .0236663
statewtpat~d |          5    .0057738    .0099923          0   .0231804
statekogan~d |          5    .0043118    .0062183          0   .0135394

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = Pacific

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          5    .0538307    .1022885   .0004011   .2362615
statewtpat~d |          5    .0651385    .1333825          0   .3033634
statekogan~d |          5    .0670729     .127212          0   .2934223

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = South Atlantic

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          8    .0190533    .0132674   .0012034   .0381067
statewtpat~d |          8    .0080614    .0056922          0   .0167537
statekogan~d |          8    .0299148    .0295822   .0054561   .0926694

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = West North Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          6    .0055489    .0058592   .0004011   .0160449
statewtpat~d |          6    .0017147    .0020078          0   .0053566
statekogan~d |          6    .0119643    .0216951   .0000882   .0557111

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015, division = West South Central

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
statepatpe~d |          3    .0147078    .0217286   .0004011   .0397112
statewtpat~d |          3    .0245308    .0405215          0   .0713023
statekogan~d |          3    .0136508    .0119511          0   .0222285


. 
. ** return to the previous datasets, before I updated Table A7 in order to keep other part consistent
. 
. use before_merge_non_csa_data, clear

. 
. ** Sumarizing overall activity in top 10 CSAs--Table 8
. 
. sort app_period csa_title

. by app_period: list csa_title csapatperiod csawtpatperiod csakoganpatperiod if (csa_code==172 | csa_code==216 | ///
> csa_code==500 | csa_code==122 | csa_code==348 | csa_code==184 | csa_code==548 | csa_code==176 | csa_code==408 | csa_co
> de==488) 

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000

     +-----------------------------------------------------------------------------------+
     | csa_title                                          csapat~d   csawtp~d   csakog~d |
     |-----------------------------------------------------------------------------------|
  6. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0199361   .0245024    .007269 |
 21. | Charlotte-Concord, NC-SC                           .0028211   .0040481   .0041883 |
 23. | Chicago-Naperville, IL-IN-WI                       .0338537   .0562433   .0285481 |
 25. | Cleveland-Akron-Canton, OH                         .0240737   .0131453   .0062379 |
 37. | Denver-Aurora, CO                                   .022193   .0189352   .0271047 |
     |-----------------------------------------------------------------------------------|
 87. | Los Angeles-Long Beach, CA                         .0244499   .0309204   .0034764 |
113. | New York-Newark, NY-NJ-CT-PA                       .1340982   .1462062   .3463442 |
141. | San Jose-San Francisco-Oakland, CA                 .0851984   .1149086   .0835953 |
143. | Seattle-Tacoma, WA                                 .0189957   .0201829   .0181257 |
162. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA     .0400602   .0465158   .0307273 |
     +-----------------------------------------------------------------------------------+

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005

     +-----------------------------------------------------------------------------------+
     | csa_title                                          csapat~d   csawtp~d   csakog~d |
     |-----------------------------------------------------------------------------------|
  6. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0260444      .0368   .0135542 |
 21. | Charlotte-Concord, NC-SC                           .0173189   .0149197   .1096961 |
 23. | Chicago-Naperville, IL-IN-WI                       .0616076   .0579481   .0447145 |
 25. | Cleveland-Akron-Canton, OH                         .0277631   .0181005   .0048591 |
 37. | Denver-Aurora, CO                                   .019963   .0143218   .0120118 |
     |-----------------------------------------------------------------------------------|
 87. | Los Angeles-Long Beach, CA                         .0207562   .0279229   .0088557 |
113. | New York-Newark, NY-NJ-CT-PA                       .1160761   .0781618   .1976592 |
141. | San Jose-San Francisco-Oakland, CA                 .1065574    .162187   .1477211 |
143. | Seattle-Tacoma, WA                                 .0252512   .0245186    .016653 |
162. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA     .0343733   .0600656   .0262122 |
     +-----------------------------------------------------------------------------------+

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010

     +-----------------------------------------------------------------------------------+
     | csa_title                                          csapat~d   csawtp~d   csakog~d |
     |-----------------------------------------------------------------------------------|
  6. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0198176   .0181138   .0109377 |
 21. | Charlotte-Concord, NC-SC                             .02252   .0318213   .0872524 |
 23. | Chicago-Naperville, IL-IN-WI                       .0745412     .07349   .0437054 |
 25. | Cleveland-Akron-Canton, OH                         .0269114   .0229559   .0029074 |
 37. | Denver-Aurora, CO                                  .0210562   .0116474   .0126434 |
     |-----------------------------------------------------------------------------------|
 87. | Los Angeles-Long Beach, CA                          .027587   .0503284   .0071742 |
113. | New York-Newark, NY-NJ-CT-PA                       .0954847   .0636807   .1443908 |
141. | San Jose-San Francisco-Oakland, CA                 .1568517   .2128163   .2496876 |
143. | Seattle-Tacoma, WA                                 .0228578   .0245629   .0240678 |
162. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA     .0323162   .0330408   .0139757 |
     +-----------------------------------------------------------------------------------+

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015

     +-----------------------------------------------------------------------------------+
     | csa_title                                          csapat~d   csawtp~d   csakog~d |
     |-----------------------------------------------------------------------------------|
  6. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0284797   .0125431    .020833 |
 21. | Charlotte-Concord, NC-SC                           .0421179   .0163708   .1365987 |
 23. | Chicago-Naperville, IL-IN-WI                       .0385078   .0297005   .0435725 |
 25. | Cleveland-Akron-Canton, OH                         .0168472   .0067133    .002672 |
 37. | Denver-Aurora, CO                                  .0128359   .0049007   .0062561 |
     |-----------------------------------------------------------------------------------|
 87. | Los Angeles-Long Beach, CA                         .0180505   .0365685   .0093375 |
113. | New York-Newark, NY-NJ-CT-PA                       .0565584   .0565881   .0572103 |
141. | San Jose-San Francisco-Oakland, CA                  .182511    .215199   .2563498 |
143. | Seattle-Tacoma, WA                                 .0184517   .0172023   .0281923 |
162. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA     .0397112    .022443   .0407657 |
     +-----------------------------------------------------------------------------------+


. 
. ** Fastest patenting growing overall--Unused
. 
. foreach v of varlist csapatperiod-csapatperiod_it csapatperiod_bc csapatperiod_pi {
  2.    gen `v'1 = `v' if app_period==2000
  3.    gen `v'4 = `v' if app_period==2015
  4.    replace `v'1 = 0 if `v'1==.
  5.    replace `v'4 = 0 if `v'4==.
  6.    by csa_code, sort: egen `v'start=max(`v'1) 
  7.    by csa_code, sort: egen `v'end=max(`v'4)
  8.    gen `v'diff=`v'end-`v'start
  9.    by csa_code, sort: drop if _n~=1
 10.    sort `v'diff
 11.    des `v', short full
 12.    list csa_title `v'diff in -5/l 
 13.    list csa_title `v'diff in 1/5 
 14.    use csa_year_data_temp2, clear
 15. }
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod    float   %9.0g                 

     +-------------------------------------------------------------+
     | csa_title                                          csapat~f |
     |-------------------------------------------------------------|
162. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0085437 |
163. | Las Vegas-Henderson, NV-AZ                         .0117824 |
164. | Bloomington-Pontiac, IL                            .0328921 |
165. | Charlotte-Concord, NC-SC                           .0392968 |
166. | San Jose-San Francisco-Oakland, CA                 .0973126 |
     +-------------------------------------------------------------+

     +------------------------------------------------------+
     | csa_title                                  csapatp~f |
     |------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA               -.0775398 |
  2. | Philadelphia-Reading-Camden, PA-NJ-DE-MD   -.0118753 |
  3. | Denver-Aurora, CO                           -.009357 |
  4. | Dallas-Fort Worth, TX-OK                   -.0086047 |
  5. | Houston-The Woodlands, TX                  -.0077494 |
     +------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_small
                float   %9.0g                 

     +-------------------------------------------------+
     | csa_title                              csapat~f |
     |-------------------------------------------------|
162. | Nashville-Davidson--Murfreesboro, TN          0 |
163. | DeRidder-Fort Polk South, LA                  0 |
164. | Toledo-Port Clinton, OH                       0 |
165. | Seattle-Tacoma, WA                      .000025 |
166. | Grand Rapids-Wyoming-Muskegon, MI      .0004011 |
     +-------------------------------------------------+

     +------------------------------------------------------------+
     | csa_title                                        csapatp~f |
     |------------------------------------------------------------|
  1. | Portland-Vancouver-Salem, OR-WA                  -.0058054 |
  2. | San Jose-San Francisco-Oakland, CA               -.0031224 |
  3. | New York-Newark, NY-NJ-CT-PA                     -.0019939 |
  4. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA   -.0016427 |
  5. | Los Angeles-Long Beach, CA                       -.0009404 |
     +------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_medium
                float   %9.0g                 

     +----------------------------------------------------+
     | csa_title                                 csapat~f |
     |----------------------------------------------------|
162. | Salt Lake City-Provo-Orem, UT             .0010652 |
163. | Las Vegas-Henderson, NV-AZ                .0026697 |
164. | Minneapolis-St. Paul, MN-WI               .0037849 |
165. | St. Louis-St. Charles-Farmington, MO-IL   .0060168 |
166. | San Jose-San Francisco-Oakland, CA        .0347649 |
     +----------------------------------------------------+

     +------------------------------------------------------------+
     | csa_title                                        csapatp~f |
     |------------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA                     -.0160513 |
  2. | Denver-Aurora, CO                                -.0136297 |
  3. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA   -.0104823 |
  4. | Cleveland-Akron-Canton, OH                       -.0097831 |
  5. | Houston-The Woodlands, TX                         -.004865 |
     +------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_large
                float   %9.0g                 

     +-----------------------------------------------------------+
     | csa_title                                        csapat~f |
     |-----------------------------------------------------------|
162. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA   .0062783 |
163. | Chicago-Naperville, IL-IN-WI                     .0109169 |
164. | Bloomington-Pontiac, IL                          .0328921 |
165. | San Jose-San Francisco-Oakland, CA               .0391055 |
166. | Charlotte-Concord, NC-SC                         .0391719 |
     +-----------------------------------------------------------+

     +------------------------------------------------------+
     | csa_title                                  csapatp~f |
     |------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA               -.0317131 |
  2. | Philadelphia-Reading-Camden, PA-NJ-DE-MD   -.0051163 |
  3. | Raleigh-Durham-Chapel Hill, NC             -.0031473 |
  4. | Albany-Schenectady, NY                     -.0028211 |
  5. | Salt Lake City-Provo-Orem, UT              -.0028211 |
     +------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_sifi
                float   %9.0g                 

     +-----------------------------------------------------------+
     | csa_title                                        csapat~f |
     |-----------------------------------------------------------|
162. | Seattle-Tacoma, WA                               .0024067 |
163. | San Jose-San Francisco-Oakland, CA               .0029077 |
164. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA   .0032589 |
165. | Dallas-Fort Worth, TX-OK                         .0040362 |
166. | Charlotte-Concord, NC-SC                         .0371663 |
     +-----------------------------------------------------------+

     +-------------------------------------------------------+
     | csa_title                                   csapatp~f |
     |-------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA                -.0231466 |
  2. | Philadelphia-Reading-Camden, PA-NJ-DE-MD    -.0032355 |
  3. | Chicago-Naperville, IL-IN-WI                -.0010785 |
  4. | Greensboro--Winston-Salem--High Point, NC   -.0005642 |
  5. | Madison-Janesville-Beloit, WI               -.0003762 |
     +-------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_payments
                float   %9.0g                 

     +----------------------------------------------------+
     | csa_title                                 csapat~f |
     |----------------------------------------------------|
162. | St. Louis-St. Charles-Farmington, MO-IL    .002675 |
163. | Las Vegas-Henderson, NV-AZ                .0041017 |
164. | Bloomington-Pontiac, IL                   .0079556 |
165. | Charlotte-Concord, NC-SC                  .0145217 |
166. | San Jose-San Francisco-Oakland, CA         .047866 |
     +----------------------------------------------------+

     +------------------------------------------------------+
     | csa_title                                  csapatp~f |
     |------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA               -.0231796 |
  2. | Philadelphia-Reading-Camden, PA-NJ-DE-MD   -.0069813 |
  3. | Dallas-Fort Worth, TX-OK                   -.0034952 |
  4. | Houston-The Woodlands, TX                   -.003094 |
  5. | Denver-Aurora, CO                          -.0028737 |
     +------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_banking
                float   %9.0g                 

     +-----------------------------------------------------+
     | csa_title                                  csapat~f |
     |-----------------------------------------------------|
162. | Chicago-Naperville, IL-IN-WI               .0013899 |
163. | Miami-Fort Lauderdale-Port St. Lucie, FL   .0014414 |
164. | Boston-Worcester-Providence, MA-RI-NH-CT   .0014913 |
165. | Bloomington-Pontiac, IL                    .0024067 |
166. | Charlotte-Concord, NC-SC                   .0032589 |
     +-----------------------------------------------------+

     +------------------------------------------------------------+
     | csa_title                                        csapatp~f |
     |------------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA                     -.0141939 |
  2. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA    -.001969 |
  3. | Philadelphia-Reading-Camden, PA-NJ-DE-MD         -.0012916 |
  4. | Houston-The Woodlands, TX                        -.0011285 |
  5. | Cleveland-Akron-Canton, OH                       -.0008904 |
     +------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_other
                float   %9.0g                 

     +-------------------------------------------------------------+
     | csa_title                                          csapat~f |
     |-------------------------------------------------------------|
162. | Las Vegas-Henderson, NV-AZ                         .0083354 |
163. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0093225 |
164. | Bloomington-Pontiac, IL                            .0272764 |
165. | Charlotte-Concord, NC-SC                           .0277774 |
166. | San Jose-San Francisco-Oakland, CA                 .0652907 |
     +-------------------------------------------------------------+

     +------------------------------------------+
     | csa_title                      csapatp~f |
     |------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA   -.0548161 |
  2. | Los Angeles-Long Beach, CA     -.0081653 |
  3. | Denver-Aurora, CO              -.0072749 |
  4. | Dallas-Fort Worth, TX-OK       -.0063845 |
  5. | Cleveland-Akron-Canton, OH     -.0062846 |
     +------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_bank
                float   %9.0g                 

     +-----------------------------------------------+
     | csa_title                            csapat~f |
     |-----------------------------------------------|
162. | Portland-Vancouver-Salem, OR-WA      .0020056 |
163. | Seattle-Tacoma, WA                   .0022187 |
164. | San Jose-San Francisco-Oakland, CA   .0031208 |
165. | Dallas-Fort Worth, TX-OK             .0040362 |
166. | Charlotte-Concord, NC-SC             .0369782 |
     +-----------------------------------------------+

     +------------------------------------------------------------+
     | csa_title                                        csapatp~f |
     |------------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA                     -.0057437 |
  2. | Philadelphia-Reading-Camden, PA-NJ-DE-MD          -.004364 |
  3. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA    -.003863 |
  4. | Greensboro--Winston-Salem--High Point, NC        -.0005642 |
  5. | Milwaukee-Racine-Waukesha, WI                    -.0005642 |
     +------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_capmkt
                float   %9.0g                 

     +-----------------------------------------------------+
     | csa_title                                  csapat~f |
     |-----------------------------------------------------|
162. | Cleveland-Akron-Canton, OH                 .0022187 |
163. | Boston-Worcester-Providence, MA-RI-NH-CT   .0033089 |
164. | Hartford-West Hartford, CT                 .0040362 |
165. | Chicago-Naperville, IL-IN-WI               .0132105 |
166. | Bloomington-Pontiac, IL                    .0328921 |
     +-----------------------------------------------------+

     +------------------------------------------------------+
     | csa_title                                  csapatp~f |
     |------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA               -.0434089 |
  2. | San Jose-San Francisco-Oakland, CA          -.004364 |
  3. | Minneapolis-St. Paul, MN-WI                 -.002445 |
  4. | Salt Lake City-Provo-Orem, UT               -.002445 |
  5. | Philadelphia-Reading-Camden, PA-NJ-DE-MD   -.0018808 |
     +------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_pay
                float   %9.0g                 

     +-----------------------------------------------------------+
     | csa_title                                        csapat~f |
     |-----------------------------------------------------------|
162. | New York-Newark, NY-NJ-CT-PA                     .0029694 |
163. | Minneapolis-St. Paul, MN-WI                      .0052146 |
164. | St. Louis-St. Charles-Farmington, MO-IL          .0100281 |
165. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA   .0109802 |
166. | San Jose-San Francisco-Oakland, CA               .0855375 |
     +-----------------------------------------------------------+

     +--------------------------------------------------------------+
     | csa_title                                          csapatp~f |
     |--------------------------------------------------------------|
  1. | Denver-Aurora, CO                                  -.0133667 |
  2. | Omaha-Council Bluffs-Fremont, NE-IA                -.0043257 |
  3. | Houston-The Woodlands, TX                          -.0037365 |
  4. | Columbus-Marion-Zanesville, OH                     -.0011035 |
  5. | Atlanta--Athens-Clarke County--Sandy Springs, GA   -.0006774 |
     +--------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_it float   %9.0g                 

     +-------------------------------------------------------------+
     | csa_title                                          csapat~f |
     |-------------------------------------------------------------|
162. | Miami-Fort Lauderdale-Port St. Lucie, FL           .0024801 |
163. | Denver-Aurora, CO                                  .0025932 |
164. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0077547 |
165. | Las Vegas-Henderson, NV-AZ                         .0117824 |
166. | San Jose-San Francisco-Oakland, CA                 .0130183 |
     +-------------------------------------------------------------+

     +------------------------------------------------------------+
     | csa_title                                        csapatp~f |
     |------------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA                     -.0313566 |
  2. | Dallas-Fort Worth, TX-OK                         -.0115624 |
  3. | Chicago-Naperville, IL-IN-WI                     -.0096715 |
  4. | Cleveland-Akron-Canton, OH                       -.0092571 |
  5. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA    -.008405 |
     +------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_bc float   %9.0g                 

     +-----------------------------------------------------+
     | csa_title                                  csapat~f |
     |-----------------------------------------------------|
162. | Boston-Worcester-Providence, MA-RI-NH-CT   .0035219 |
163. | Hartford-West Hartford, CT                 .0040362 |
164. | Chicago-Naperville, IL-IN-WI               .0133104 |
165. | Bloomington-Pontiac, IL                    .0328921 |
166. | Charlotte-Concord, NC-SC                   .0374043 |
     +-----------------------------------------------------+

     +------------------------------------------------------------+
     | csa_title                                        csapatp~f |
     |------------------------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA                     -.0491526 |
  2. | Philadelphia-Reading-Camden, PA-NJ-DE-MD         -.0062448 |
  3. | Washington-Baltimore-Arlington, DC-MD-VA-WV-PA   -.0029242 |
  4. | Salt Lake City-Provo-Orem, UT                     -.002445 |
  5. | Minneapolis-St. Paul, MN-WI                        -.00242 |
     +------------------------------------------------------------+
(498 missing values generated)
(498 missing values generated)
(498 real changes made)
(498 real changes made)
(498 observations deleted)

Variable      Storage   Display    Value
    name         type    format    label      Variable label
------------------------------------------------------------------------------------------------------------------------
csapatperiod_pi float   %9.0g                 

     +-------------------------------------------------------------+
     | csa_title                                          csapat~f |
     |-------------------------------------------------------------|
162. | Minneapolis-St. Paul, MN-WI                        .0039347 |
163. | Atlanta--Athens-Clarke County--Sandy Springs, GA   .0070773 |
164. | St. Louis-St. Charles-Farmington, MO-IL            .0085235 |
165. | Las Vegas-Henderson, NV-AZ                         .0117824 |
166. | San Jose-San Francisco-Oakland, CA                 .0985558 |
     +-------------------------------------------------------------+

     +------------------------------------------+
     | csa_title                      csapatp~f |
     |------------------------------------------|
  1. | New York-Newark, NY-NJ-CT-PA   -.0283872 |
  2. | Dallas-Fort Worth, TX-OK       -.0117005 |
  3. | Denver-Aurora, CO              -.0107734 |
  4. | Cleveland-Akron-Canton, OH     -.0092571 |
  5. | Chicago-Naperville, IL-IN-WI   -.0086562 |
     +------------------------------------------+

. 
. ** By SF--Table A-14, Panel A
. 
. gen SF=(csa_code==488)

. sort SF

. by app_period, sort: sum csapatperiod-csakoganpatperiod_it if SF==1

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .0851984           .   .0851984   .0851984
csapatperi~l |          1    .0043257           .   .0043257   .0043257
csapatperi~m |          1    .0282114           .   .0282114   .0282114
csapatperi~e |          1    .0150461           .   .0150461   .0150461
csapatper~fi |          1    .0015046           .   .0015046   .0015046
-------------+---------------------------------------------------------
csapatperi~s |          1    .0300522           .   .0300522   .0300522
csapatperi~g |          1      .00489           .     .00489     .00489
csapatperi~r |          1    .0650743           .   .0650743   .0650743
csapatperi~k |          1    .0016927           .   .0016927   .0016927
csapatper~kt |          1    .0067707           .   .0067707   .0067707
-------------+---------------------------------------------------------
csapatperi~y |          1     .007523           .    .007523    .007523
csapatper~it |          1     .069212           .    .069212    .069212
csawtpatpe~d |          1    .1149086           .   .1149086   .1149086
csawtpatpe~l |          1    .0082387           .   .0082387   .0082387
csawtpatpe~m |          1    .0328811           .   .0328811   .0328811
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0143334           .   .0143334   .0143334
csawtpatpe~i |          1     .002815           .    .002815    .002815
csawtpatpe~s |          1    .0395939           .   .0395939   .0395939
csawtpatpe~g |          1    .0056096           .   .0056096   .0056096
csawtpatpe~r |          1    .0911664           .   .0911664   .0911664
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0028357           .   .0028357   .0028357
csawtpatp~kt |          1    .0064056           .   .0064056   .0064056
csawtpatpe~y |          1     .015016           .    .015016    .015016
csawtpatp~it |          1    .0906513           .   .0906513   .0906513
csakoganpa~d |          1    .0835953           .   .0835953   .0835953
-------------+---------------------------------------------------------
csak~d_small |          1    .0003131           .   .0003131   .0003131
csakoganpa.. |          1    .0301982           .   .0301982   .0301982
csak~d_large |          1    .0501094           .   .0501094   .0501094
csako~d_sifi |          1    .0304929           .   .0304929   .0304929
csakoganpa.. |          1    .0319555           .   .0319555   .0319555
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0018519           .   .0018519   .0018519
csak~d_other |          1    .0704538           .   .0704538   .0704538
csako~d_bank |          1    .0304929           .   .0304929   .0304929
csakoganpa.. |          1    .0069952           .   .0069952   .0069952
csakog~d_pay |          1     .006314           .    .006314    .006314
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0397932           .   .0397932   .0397932

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .1065574           .   .1065574   .1065574
csapatperi~l |          1    .0023797           .   .0023797   .0023797
csapatperi~m |          1    .0506346           .   .0506346   .0506346
csapatperi~e |          1    .0170545           .   .0170545   .0170545
csapatper~fi |          1    .0019831           .   .0019831   .0019831
-------------+---------------------------------------------------------
csapatperi~s |          1    .0430013           .   .0430013   .0430013
csapatperi~g |          1    .0055526           .   .0055526   .0055526
csapatperi~r |          1    .0749603           .   .0749603   .0749603
csapatperi~k |          1    .0019831           .   .0019831   .0019831
csapatper~kt |          1    .0040984           .   .0040984   .0040984
-------------+---------------------------------------------------------
csapatperi~y |          1    .0237969           .   .0237969   .0237969
csapatper~it |          1     .076679           .    .076679    .076679
csawtpatpe~d |          1     .162187           .    .162187    .162187
csawtpatpe~l |          1    .0053921           .   .0053921   .0053921
csawtpatpe~m |          1    .0680003           .   .0680003   .0680003
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0226245           .   .0226245   .0226245
csawtpatpe~i |          1    .0030476           .   .0030476   .0030476
csawtpatpe~s |          1    .0743426           .   .0743426   .0743426
csawtpatpe~g |          1     .007044           .    .007044    .007044
csawtpatpe~r |          1    .1125601           .   .1125601   .1125601
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0030476           .   .0030476   .0030476
csawtpatp~kt |          1    .0025348           .   .0025348   .0025348
csawtpatpe~y |          1    .0438758           .   .0438758   .0438758
csawtpatp~it |          1    .1127287           .   .1127287   .1127287
csakoganpa~d |          1    .1477211           .   .1477211   .1477211
-------------+---------------------------------------------------------
csak~d_small |          1    .0001725           .   .0001725   .0001725
csakoganpa.. |          1     .107974           .    .107974    .107974
csak~d_large |          1    .0372966           .   .0372966   .0372966
csako~d_sifi |          1    .0242797           .   .0242797   .0242797
csakoganpa.. |          1    .0644007           .   .0644007   .0644007
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0046993           .   .0046993   .0046993
csak~d_other |          1    .1082707           .   .1082707   .1082707
csako~d_bank |          1    .0242797           .   .0242797   .0242797
csakoganpa.. |          1    .0030534           .   .0030534   .0030534
csakog~d_pay |          1    .0785379           .   .0785379   .0785379
-------------+---------------------------------------------------------
csakoga~d_it |          1      .04185           .     .04185     .04185

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .1568517           .   .1568517   .1568517
csapatperi~l |          1    .0023646           .   .0023646   .0023646
csapatperi~m |          1    .0539354           .   .0539354   .0539354
csapatperi~e |          1    .0487558           .   .0487558   .0487558
csapatper~fi |          1    .0034906           .   .0034906   .0034906
-------------+---------------------------------------------------------
csapatperi~s |          1    .0664971           .   .0664971   .0664971
csapatperi~g |          1    .0054048           .   .0054048   .0054048
csapatperi~r |          1    .1151897           .   .1151897   .1151897
csapatperi~k |          1    .0038284           .   .0038284   .0038284
csapatper~kt |          1    .0063056           .   .0063056   .0063056
-------------+---------------------------------------------------------
csapatperi~y |          1     .051233           .    .051233    .051233
csapatper~it |          1    .0954847           .   .0954847   .0954847
csawtpatpe~d |          1    .2128163           .   .2128163   .2128163
csawtpatpe~l |          1    .0046245           .   .0046245   .0046245
csawtpatpe~m |          1    .0720168           .   .0720168   .0720168
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0729512           .   .0729512   .0729512
csawtpatpe~i |          1    .0031461           .   .0031461   .0031461
csawtpatpe~s |          1     .095479           .    .095479    .095479
csawtpatpe~g |          1    .0021711           .   .0021711   .0021711
csawtpatpe~r |          1    .1565066           .   .1565066   .1565066
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0038642           .   .0038642   .0038642
csawtpatp~kt |          1    .0041816           .   .0041816   .0041816
csawtpatpe~y |          1    .0894843           .   .0894843   .0894843
csawtpatp~it |          1    .1152862           .   .1152862   .1152862
csakoganpa~d |          1    .2496876           .   .2496876   .2496876
-------------+---------------------------------------------------------
csak~d_small |          1    .0000294           .   .0000294   .0000294
csakoganpa.. |          1    .0582401           .   .0582401   .0582401
csak~d_large |          1    .1903159           .   .1903159   .1903159
csako~d_sifi |          1    .0447301           .   .0447301   .0447301
csakoganpa.. |          1    .1078333           .   .1078333   .1078333
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0087405           .   .0087405   .0087405
csak~d_other |          1     .189249           .    .189249    .189249
csako~d_bank |          1    .0447301           .   .0447301   .0447301
csakoganpa.. |          1    .0040461           .   .0040461   .0040461
csakog~d_pay |          1    .1118071           .   .1118071   .1118071
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0891043           .   .0891043   .0891043

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1     .182511           .    .182511    .182511
csapatperi~l |          1    .0012034           .   .0012034   .0012034
csapatperi~m |          1    .0629763           .   .0629763   .0629763
csapatperi~e |          1    .0541516           .   .0541516   .0541516
csapatper~fi |          1    .0044124           .   .0044124   .0044124
-------------+---------------------------------------------------------
csapatperi~s |          1    .0779182           .   .0779182   .0779182
csapatperi~g |          1    .0060168           .   .0060168   .0060168
csapatperi~r |          1     .130365           .    .130365    .130365
csapatperi~k |          1    .0048135           .   .0048135   .0048135
csapatper~kt |          1    .0024067           .   .0024067   .0024067
-------------+---------------------------------------------------------
csapatperi~y |          1    .0930606           .   .0930606   .0930606
csapatper~it |          1    .0822302           .   .0822302   .0822302
csawtpatpe~d |          1     .215199           .    .215199    .215199
csawtpatpe~l |          1    .0005802           .   .0005802   .0005802
csawtpatpe~m |          1    .0960573           .   .0960573   .0960573
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0381539           .   .0381539   .0381539
csawtpatpe~i |          1    .0037929           .   .0037929   .0037929
csawtpatpe~s |          1    .0956418           .   .0956418   .0956418
csawtpatpe~g |          1    .0049434           .   .0049434   .0049434
csawtpatpe~r |          1    .1552418           .   .1552418   .1552418
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0037929           .   .0037929   .0037929
csawtpatp~kt |          1           0           .          0          0
csawtpatpe~y |          1    .1111152           .   .1111152   .1111152
csawtpatp~it |          1    .1002909           .   .1002909   .1002909
csakoganpa~d |          1    .2563498           .   .2563498   .2563498
-------------+---------------------------------------------------------
csak~d_small |          1           0           .          0          0
csakoganpa.. |          1    .0542151           .   .0542151   .0542151
csak~d_large |          1    .1934216           .   .1934216   .1934216
csako~d_sifi |          1    .0498312           .   .0498312   .0498312
csakoganpa.. |          1    .1277797           .   .1277797   .1277797
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0067815           .   .0067815   .0067815
csak~d_other |          1    .1631706           .   .1631706   .1631706
csako~d_bank |          1    .0498312           .   .0498312   .0498312
csakoganpa.. |          1    .0002966           .   .0002966   .0002966
csakog~d_pay |          1    .1772308           .   .1772308   .1772308
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0289913           .   .0289913   .0289913


. 
. ** By NYC--Table A-14, Panel B
. 
. gen NY=(csa_code==408)

. sort NY

. by app_period, sort: sum csapatperiod-csakoganpatperiod_it if NY==1

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .1340982           .   .1340982   .1340982
csapatperi~l |          1    .0031973           .   .0031973   .0031973
csapatperi~m |          1    .0240737           .   .0240737   .0240737
csapatperi~e |          1    .0449502           .   .0449502   .0449502
csapatper~fi |          1    .0259545           .   .0259545   .0259545
-------------+---------------------------------------------------------
csapatperi~s |          1    .0448775           .   .0448775   .0448775
csapatperi~g |          1    .0157984           .   .0157984   .0157984
csapatperi~r |          1    .0957307           .   .0957307   .0957307
csapatperi~k |          1    .0101561           .   .0101561   .0101561
csapatper~kt |          1     .047019           .    .047019    .047019
-------------+---------------------------------------------------------
csapatperi~y |          1    .0054542           .   .0054542   .0054542
csapatper~it |          1    .0714689           .   .0714689   .0714689
csawtpatpe~d |          1    .1462062           .   .1462062   .1462062
csawtpatpe~l |          1    .0019423           .   .0019423   .0019423
csawtpatpe~m |          1    .0250682           .   .0250682   .0250682
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0465206           .   .0465206   .0465206
csawtpatpe~i |          1    .0232108           .   .0232108   .0232108
csawtpatpe~s |          1    .0553313           .   .0553313   .0553313
csawtpatpe~g |          1    .0115699           .   .0115699   .0115699
csawtpatpe~r |          1    .1068594           .   .1068594   .1068594
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0179643           .   .0179643   .0179643
csawtpatp~kt |          1    .0369084           .   .0369084   .0369084
csawtpatpe~y |          1     .009687           .    .009687    .009687
csawtpatp~it |          1    .0816466           .   .0816466   .0816466
csakoganpa~d |          1    .3463442           .   .3463442   .3463442
-------------+---------------------------------------------------------
csak~d_small |          1    .0002601           .   .0002601   .0002601
csakoganpa.. |          1    .0230535           .   .0230535   .0230535
csak~d_large |          1    .3230113           .   .3230113   .3230113
csako~d_sifi |          1     .275714           .    .275714    .275714
csakoganpa.. |          1    .1219978           .   .1219978   .1219978
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0378067           .   .0378067   .0378067
csak~d_other |          1     .244066           .    .244066    .244066
csako~d_bank |          1    .1141623           .   .1141623   .1141623
csakoganpa.. |          1    .2142197           .   .2142197   .2142197
csakog~d_pay |          1    .0089693           .   .0089693   .0089693
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0089929           .   .0089929   .0089929

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .1160761           .   .1160761   .1160761
csapatperi~l |          1    .0021153           .   .0021153   .0021153
csapatperi~m |          1    .0204918           .   .0204918   .0204918
csapatperi~e |          1    .0358276           .   .0358276   .0358276
csapatper~fi |          1    .0186409           .   .0186409   .0186409
-------------+---------------------------------------------------------
csapatperi~s |          1    .0415624           .   .0415624   .0415624
csapatperi~g |          1    .0137493           .   .0137493   .0137493
csapatperi~r |          1    .0786621           .   .0786621   .0786621
csapatperi~k |          1    .0107086           .   .0107086   .0107086
csapatper~kt |          1    .0445531           .   .0445531   .0445531
-------------+---------------------------------------------------------
csapatperi~y |          1    .0040984           .   .0040984   .0040984
csapatper~it |          1     .056716           .    .056716    .056716
csawtpatpe~d |          1    .0781618           .   .0781618   .0781618
csawtpatpe~l |          1    .0014151           .   .0014151   .0014151
csawtpatpe~m |          1    .0097221           .   .0097221   .0097221
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0195364           .   .0195364   .0195364
csawtpatpe~i |          1     .005314           .    .005314    .005314
csawtpatpe~s |          1    .0333501           .   .0333501   .0333501
csawtpatpe~g |          1    .0062689           .   .0062689   .0062689
csawtpatpe~r |          1    .0503931           .   .0503931   .0503931
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0066885           .   .0066885   .0066885
csawtpatp~kt |          1     .016216           .    .016216    .016216
csawtpatpe~y |          1    .0022328           .   .0022328   .0022328
csawtpatp~it |          1    .0530245           .   .0530245   .0530245
csakoganpa~d |          1    .1976592           .   .1976592   .1976592
-------------+---------------------------------------------------------
csak~d_small |          1     .000043           .    .000043    .000043
csakoganpa.. |          1    .0251557           .   .0251557   .0251557
csak~d_large |          1    .1720872           .   .1720872   .1720872
csako~d_sifi |          1    .1468745           .   .1468745   .1468745
csakoganpa.. |          1    .0682859           .   .0682859   .0682859
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0247583           .   .0247583   .0247583
csak~d_other |          1    .1391257           .   .1391257   .1391257
csako~d_bank |          1    .0786121           .   .0786121   .0786121
csakoganpa.. |          1    .1037294           .   .1037294   .1037294
csakog~d_pay |          1    .0090987           .   .0090987   .0090987
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0062189           .   .0062189   .0062189

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .0954847           .   .0954847   .0954847
csapatperi~l |          1    .0015764           .   .0015764   .0015764
csapatperi~m |          1    .0155388           .   .0155388   .0155388
csapatperi~e |          1     .029276           .    .029276    .029276
csapatper~fi |          1     .013512           .    .013512    .013512
-------------+---------------------------------------------------------
csapatperi~s |          1    .0343544           .   .0343544   .0343544
csapatperi~g |          1    .0111474           .   .0111474   .0111474
csapatperi~r |          1    .0654206           .   .0654206   .0654206
csapatperi~k |          1    .0076568           .   .0076568   .0076568
csapatper~kt |          1    .0319784           .   .0319784   .0319784
-------------+---------------------------------------------------------
csapatperi~y |          1    .0059678           .   .0059678   .0059678
csapatper~it |          1    .0498818           .   .0498818   .0498818
csawtpatpe~d |          1    .0636807           .   .0636807   .0636807
csawtpatpe~l |          1    .0038969           .   .0038969   .0038969
csawtpatpe~m |          1    .0059426           .   .0059426   .0059426
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0170158           .   .0170158   .0170158
csawtpatpe~i |          1    .0026673           .   .0026673   .0026673
csawtpatpe~s |          1    .0230057           .   .0230057   .0230057
csawtpatpe~g |          1    .0031839           .   .0031839   .0031839
csawtpatpe~r |          1    .0467327           .   .0467327   .0467327
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0040746           .   .0040746   .0040746
csawtpatp~kt |          1    .0095812           .   .0095812   .0095812
csawtpatpe~y |          1    .0039174           .   .0039174   .0039174
csawtpatp~it |          1    .0461075           .   .0461075   .0461075
csakoganpa~d |          1    .1443908           .   .1443908   .1443908
-------------+---------------------------------------------------------
csak~d_small |          1    .0000116           .   .0000116   .0000116
csakoganpa.. |          1    .0276533           .   .0276533   .0276533
csak~d_large |          1    .1138428           .   .1138428   .1138428
csako~d_sifi |          1    .0829833           .   .0829833   .0829833
csakoganpa.. |          1    .0572332           .   .0572332   .0572332
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0126679           .   .0126679   .0126679
csak~d_other |          1    .1055702           .   .1055702   .1055702
csako~d_bank |          1    .0527586           .   .0527586   .0527586
csakoganpa.. |          1    .0594306           .   .0594306   .0594306
csakog~d_pay |          1    .0232884           .   .0232884   .0232884
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0089132           .   .0089132   .0089132

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .0565584           .   .0565584   .0565584
csapatperi~l |          1    .0012034           .   .0012034   .0012034
csapatperi~m |          1    .0080225           .   .0080225   .0080225
csapatperi~e |          1    .0132371           .   .0132371   .0132371
csapatper~fi |          1    .0028079           .   .0028079   .0028079
-------------+---------------------------------------------------------
csapatperi~s |          1    .0216979           .   .0216979   .0216979
csapatperi~g |          1    .0016045           .   .0016045   .0016045
csapatperi~r |          1    .0409146           .   .0409146   .0409146
csapatperi~k |          1    .0044124           .   .0044124   .0044124
csapatper~kt |          1    .0036101           .   .0036101   .0036101
-------------+---------------------------------------------------------
csapatperi~y |          1    .0084236           .   .0084236   .0084236
csapatper~it |          1    .0401123           .   .0401123   .0401123
csawtpatpe~d |          1    .0565881           .   .0565881   .0565881
csawtpatpe~l |          1     .001178           .    .001178    .001178
csawtpatpe~m |          1    .0079695           .   .0079695   .0079695
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0055889           .   .0055889   .0055889
csawtpatpe~i |          1    .0018682           .   .0018682   .0018682
csawtpatpe~s |          1    .0185648           .   .0185648   .0185648
csawtpatpe~g |          1           0           .          0          0
csawtpatpe~r |          1    .0428609           .   .0428609   .0428609
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0038333           .   .0038333   .0038333
csawtpatp~kt |          1           0           .          0          0
csawtpatpe~y |          1    .0082692           .   .0082692   .0082692
csawtpatp~it |          1    .0444856           .   .0444856   .0444856
csakoganpa~d |          1    .0572103           .   .0572103   .0572103
-------------+---------------------------------------------------------
csak~d_small |          1           0           .          0          0
csakoganpa.. |          1     .015492           .    .015492    .015492
csak~d_large |          1    .0382483           .   .0382483   .0382483
csako~d_sifi |          1    .0181816           .   .0181816   .0181816
csakoganpa.. |          1    .0184238           .   .0184238   .0184238
-------------+---------------------------------------------------------
csakoganpa.. |          1           0           .          0          0
csak~d_other |          1    .0463724           .   .0463724   .0463724
csako~d_bank |          1    .0201087           .   .0201087   .0201087
csakoganpa.. |          1    .0031943           .   .0031943   .0031943
csakog~d_pay |          1    .0207468           .   .0207468   .0207468
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0131605           .   .0131605   .0131605


. 
. ** By Charlotte----Table A-14, Panel C
. 
. gen CLT=(csa_code==172)

. sort CLT

. by app_period, sort: sum csapatperiod-csakoganpatperiod_it if CLT==1

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2000

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .0028211           .   .0028211   .0028211
csapatperi~l |          1           0           .          0          0
csapatperi~m |          1           0           .          0          0
csapatperi~e |          1    .0009404           .   .0009404   .0009404
csapatper~fi |          1    .0009404           .   .0009404   .0009404
-------------+---------------------------------------------------------
csapatperi~s |          1    .0008213           .   .0008213   .0008213
csapatperi~g |          1    .0007523           .   .0007523   .0007523
csapatperi~r |          1    .0015046           .   .0015046   .0015046
csapatperi~k |          1    .0011285           .   .0011285   .0011285
csapatper~kt |          1    .0003762           .   .0003762   .0003762
-------------+---------------------------------------------------------
csapatperi~y |          1           0           .          0          0
csapatper~it |          1    .0013165           .   .0013165   .0013165
csawtpatpe~d |          1    .0040481           .   .0040481   .0040481
csawtpatpe~l |          1           0           .          0          0
csawtpatpe~m |          1           0           .          0          0
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0017332           .   .0017332   .0017332
csawtpatpe~i |          1    .0017332           .   .0017332   .0017332
csawtpatpe~s |          1    .0010729           .   .0010729   .0010729
csawtpatpe~g |          1    .0007423           .   .0007423   .0007423
csawtpatpe~r |          1    .0026739           .   .0026739   .0026739
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0023295           .   .0023295   .0023295
csawtpatp~kt |          1    .0005698           .   .0005698   .0005698
csawtpatpe~y |          1           0           .          0          0
csawtpatp~it |          1    .0011489           .   .0011489   .0011489
csakoganpa~d |          1    .0041883           .   .0041883   .0041883
-------------+---------------------------------------------------------
csak~d_small |          1           0           .          0          0
csakoganpa.. |          1           0           .          0          0
csak~d_large |          1    .0041883           .   .0041883   .0041883
csako~d_sifi |          1    .0041883           .   .0041883   .0041883
csakoganpa.. |          1    .0007327           .   .0007327   .0007327
-------------+---------------------------------------------------------
csakoganpa.. |          1           0           .          0          0
csak~d_other |          1    .0041883           .   .0041883   .0041883
csako~d_bank |          1    .0041883           .   .0041883   .0041883
csakoganpa.. |          1           0           .          0          0
csakog~d_pay |          1           0           .          0          0
-------------+---------------------------------------------------------
csakoga~d_it |          1           0           .          0          0

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2005

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .0173189           .   .0173189   .0173189
csapatperi~l |          1           0           .          0          0
csapatperi~m |          1    .0003966           .   .0003966   .0003966
csapatperi~e |          1     .015468           .    .015468    .015468
csapatper~fi |          1    .0150714           .   .0150714   .0150714
-------------+---------------------------------------------------------
csapatperi~s |          1    .0083346           .   .0083346   .0083346
csapatperi~g |          1    .0018509           .   .0018509   .0018509
csapatperi~r |          1    .0095188           .   .0095188   .0095188
csapatperi~k |          1    .0150714           .   .0150714   .0150714
csapatper~kt |          1    .0009254           .   .0009254   .0009254
-------------+---------------------------------------------------------
csapatperi~y |          1           0           .          0          0
csapatper~it |          1    .0013221           .   .0013221   .0013221
csawtpatpe~d |          1    .0149197           .   .0149197   .0149197
csawtpatpe~l |          1           0           .          0          0
csawtpatpe~m |          1    .0000383           .   .0000383   .0000383
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0143284           .   .0143284   .0143284
csawtpatpe~i |          1    .0138049           .   .0138049   .0138049
csawtpatpe~s |          1    .0063962           .   .0063962   .0063962
csawtpatpe~g |          1    .0003664           .   .0003664   .0003664
csawtpatpe~r |          1    .0108684           .   .0108684   .0108684
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0138049           .   .0138049   .0138049
csawtpatp~kt |          1    .0003843           .   .0003843   .0003843
csawtpatpe~y |          1           0           .          0          0
csawtpatp~it |          1    .0007305           .   .0007305   .0007305
csakoganpa~d |          1    .1096961           .   .1096961   .1096961
-------------+---------------------------------------------------------
csak~d_small |          1           0           .          0          0
csakoganpa.. |          1    .0001256           .   .0001256   .0001256
csak~d_large |          1    .1095705           .   .1095705   .1095705
csako~d_sifi |          1     .109553           .    .109553    .109553
csakoganpa.. |          1     .058999           .    .058999    .058999
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0065247           .   .0065247   .0065247
csak~d_other |          1    .0637469           .   .0637469   .0637469
csako~d_bank |          1     .109553           .    .109553    .109553
csakoganpa.. |          1    .0001087           .   .0001087   .0001087
csakog~d_pay |          1           0           .          0          0
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0000344           .   .0000344   .0000344

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2010

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1      .02252           .     .02252     .02252
csapatperi~l |          1           0           .          0          0
csapatperi~m |          1     .000563           .    .000563    .000563
csapatperi~e |          1    .0206058           .   .0206058   .0206058
csapatper~fi |          1     .020268           .    .020268    .020268
-------------+---------------------------------------------------------
csapatperi~s |          1    .0104155           .   .0104155   .0104155
csapatperi~g |          1    .0015764           .   .0015764   .0015764
csapatperi~r |          1    .0144128           .   .0144128   .0144128
csapatperi~k |          1     .020268           .    .020268    .020268
csapatper~kt |          1    .0003378           .   .0003378   .0003378
-------------+---------------------------------------------------------
csapatperi~y |          1     .000563           .    .000563    .000563
csapatper~it |          1    .0013512           .   .0013512   .0013512
csawtpatpe~d |          1    .0318213           .   .0318213   .0318213
csawtpatpe~l |          1           0           .          0          0
csawtpatpe~m |          1           0           .          0          0
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0165118           .   .0165118   .0165118
csawtpatpe~i |          1    .0164633           .   .0164633   .0164633
csawtpatpe~s |          1    .0105549           .   .0105549   .0105549
csawtpatpe~g |          1    .0080884           .   .0080884   .0080884
csawtpatpe~r |          1    .0202001           .   .0202001   .0202001
-------------+---------------------------------------------------------
csawtpatpe~k |          1    .0164633           .   .0164633   .0164633
csawtpatp~kt |          1           0           .          0          0
csawtpatpe~y |          1           0           .          0          0
csawtpatp~it |          1     .015358           .    .015358    .015358
csakoganpa~d |          1    .0872524           .   .0872524   .0872524
-------------+---------------------------------------------------------
csak~d_small |          1           0           .          0          0
csakoganpa.. |          1     .005743           .    .005743    .005743
csak~d_large |          1     .081438           .    .081438    .081438
csako~d_sifi |          1    .0813899           .   .0813899   .0813899
csakoganpa.. |          1     .042035           .    .042035    .042035
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0047041           .   .0047041   .0047041
csak~d_other |          1    .0566296           .   .0566296   .0566296
csako~d_bank |          1    .0813899           .   .0813899   .0813899
csakoganpa.. |          1           0           .          0          0
csakog~d_pay |          1     .005743           .    .005743    .005743
-------------+---------------------------------------------------------
csakoga~d_it |          1    .0001196           .   .0001196   .0001196

------------------------------------------------------------------------------------------------------------------------
-> app_period = 2015

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
csapatperiod |          1    .0421179           .   .0421179   .0421179
csapatperi~l |          1           0           .          0          0
csapatperi~m |          1    .0004011           .   .0004011   .0004011
csapatperi~e |          1    .0401123           .   .0401123   .0401123
csapatper~fi |          1    .0381067           .   .0381067   .0381067
-------------+---------------------------------------------------------
csapatperi~s |          1     .015343           .    .015343    .015343
csapatperi~g |          1    .0040112           .   .0040112   .0040112
csapatperi~r |          1     .029282           .    .029282    .029282
csapatperi~k |          1    .0381067           .   .0381067   .0381067
csapatper~kt |          1    .0008022           .   .0008022   .0008022
-------------+---------------------------------------------------------
csapatperi~y |          1    .0008022           .   .0008022   .0008022
csapatper~it |          1    .0024067           .   .0024067   .0024067
csawtpatpe~d |          1    .0163708           .   .0163708   .0163708
csawtpatpe~l |          1           0           .          0          0
csawtpatpe~m |          1           0           .          0          0
-------------+---------------------------------------------------------
csawtpatpe~e |          1    .0155636           .   .0155636   .0155636
csawtpatpe~i |          1     .015214           .    .015214    .015214
csawtpatpe~s |          1    .0054605           .   .0054605   .0054605
csawtpatpe~g |          1    .0024124           .   .0024124   .0024124
csawtpatpe~r |          1    .0095394           .   .0095394   .0095394
-------------+---------------------------------------------------------
csawtpatpe~k |          1     .015214           .    .015214    .015214
csawtpatp~kt |          1           0           .          0          0
csawtpatpe~y |          1           0           .          0          0
csawtpatp~it |          1    .0011567           .   .0011567   .0011567
csakoganpa~d |          1    .1365987           .   .1365987   .1365987
-------------+---------------------------------------------------------
csak~d_small |          1           0           .          0          0
csakoganpa.. |          1    .0014109           .   .0014109   .0014109
csak~d_large |          1    .1351878           .   .1351878   .1351878
csako~d_sifi |          1    .1306758           .   .1306758   .1306758
csakoganpa.. |          1     .048472           .    .048472    .048472
-------------+---------------------------------------------------------
csakoganpa.. |          1    .0122537           .   .0122537   .0122537
csak~d_other |          1    .0989409           .   .0989409   .0989409
csako~d_bank |          1    .1306758           .   .1306758   .1306758
csakoganpa.. |          1    .0008601           .   .0008601   .0008601
csakog~d_pay |          1    .0049969           .   .0049969   .0049969
-------------+---------------------------------------------------------
csakoga~d_it |          1     .000066           .    .000066    .000066


. 
. 
. 
. 
. 
. *** FINPATHJREFEREE.TXT
. 
. clear 

. 
. * Table A-17 and A-18
. 
. use fin_addition.dta 

. drop if patent_id==.
(458 observations deleted)

. bys permco: gen temp=(_n==1)

. tab sic if temp==1, sort

   Standard |
   Industry |
Classificat |
   ion Code |      Freq.     Percent        Cum.
------------+-----------------------------------
       7372 |         30       13.95       13.95
       7370 |         23       10.70       24.65
       3674 |         20        9.30       33.95
       7373 |         12        5.58       39.53
       3663 |         11        5.12       44.65
       4813 |          9        4.19       48.84
       3577 |          7        3.26       52.09
       3572 |          5        2.33       54.42
       7374 |          5        2.33       56.74
       3576 |          4        1.86       58.60
       3578 |          4        1.86       60.47
       3661 |          4        1.86       62.33
       3571 |          3        1.40       63.72
       3579 |          3        1.40       65.12
       3711 |          3        1.40       66.51
       3845 |          3        1.40       67.91
       4812 |          3        1.40       69.30
       6794 |          3        1.40       70.70
       9997 |          3        1.40       72.09
       1381 |          2        0.93       73.02
       2911 |          2        0.93       73.95
       3570 |          2        0.93       74.88
       3600 |          2        0.93       75.81
       3679 |          2        0.93       76.74
       3812 |          2        0.93       77.67
       6282 |          2        0.93       78.60
       7371 |          2        0.93       79.53
       7389 |          2        0.93       80.47
       1389 |          1        0.47       80.93
       2060 |          1        0.47       81.40
       2111 |          1        0.47       81.86
       2522 |          1        0.47       82.33
       2670 |          1        0.47       82.79
       2761 |          1        0.47       83.26
       2820 |          1        0.47       83.72
       2836 |          1        0.47       84.19
       2840 |          1        0.47       84.65
       2860 |          1        0.47       85.12
       3060 |          1        0.47       85.58
       3490 |          1        0.47       86.05
       3523 |          1        0.47       86.51
       3531 |          1        0.47       86.98
       3540 |          1        0.47       87.44
       3559 |          1        0.47       87.91
       3580 |          1        0.47       88.37
       3620 |          1        0.47       88.84
       3630 |          1        0.47       89.30
       3672 |          1        0.47       89.77
       3721 |          1        0.47       90.23
       3760 |          1        0.47       90.70
       3824 |          1        0.47       91.16
       3844 |          1        0.47       91.63
       3861 |          1        0.47       92.09
       3942 |          1        0.47       92.56
       3944 |          1        0.47       93.02
       3990 |          1        0.47       93.49
       4888 |          1        0.47       93.95
       4899 |          1        0.47       94.42
       5000 |          1        0.47       94.88
       5045 |          1        0.47       95.35
       5047 |          1        0.47       95.81
       5812 |          1        0.47       96.28
       5961 |          1        0.47       96.74
       6099 |          1        0.47       97.21
       6200 |          1        0.47       97.67
       6211 |          1        0.47       98.14
       7323 |          1        0.47       98.60
       7990 |          1        0.47       99.07
       8731 |          1        0.47       99.53
       9995 |          1        0.47      100.00
------------+-----------------------------------
      Total |        215      100.00

. bys permco app_year: replace temp=(_n==1)
(3861 real changes made)

. 
. * Table A-17, Panel A
. 
. tab sic if temp==1, sort

   Standard |
   Industry |
Classificat |
   ion Code |      Freq.     Percent        Cum.
------------+-----------------------------------
       7372 |        405       11.76       11.76
       7370 |        394       11.44       23.21
       3674 |        385       11.18       34.39
       3663 |        184        5.34       39.73
       7373 |        169        4.91       44.64
       4813 |        137        3.98       48.62
       3577 |        113        3.28       51.90
       4812 |         82        2.38       54.28
       3711 |         81        2.35       56.64
       3572 |         79        2.29       58.93
       3576 |         76        2.21       61.14
       9997 |         70        2.03       63.17
       3578 |         62        1.80       64.97
       3661 |         59        1.71       66.69
       3845 |         57        1.66       68.34
       6794 |         54        1.57       69.91
       3679 |         53        1.54       71.45
       3812 |         42        1.22       72.67
       2911 |         38        1.10       73.77
       3570 |         38        1.10       74.88
       3600 |         38        1.10       75.98
       4888 |         36        1.05       77.03
       3579 |         35        1.02       78.04
       1381 |         32        0.93       78.97
       3571 |         32        0.93       79.90
       7374 |         22        0.64       80.54
       1389 |         21        0.61       81.15
       7389 |         20        0.58       81.73
       2111 |         19        0.55       82.28
       2522 |         19        0.55       82.83
       2670 |         19        0.55       83.39
       2840 |         19        0.55       83.94
       3060 |         19        0.55       84.49
       3523 |         19        0.55       85.04
       3531 |         19        0.55       85.59
       3559 |         19        0.55       86.15
       3620 |         19        0.55       86.70
       3721 |         19        0.55       87.25
       3760 |         19        0.55       87.80
       3824 |         19        0.55       88.35
       3844 |         19        0.55       88.91
       3942 |         19        0.55       89.46
       5961 |         19        0.55       90.01
       3621 |         18        0.52       90.53
       5047 |         18        0.52       91.05
       6282 |         18        0.52       91.58
       8742 |         18        0.52       92.10
       2860 |         17        0.49       92.59
       3490 |         17        0.49       93.09
       3672 |         17        0.49       93.58
       7371 |         16        0.46       94.05
       3990 |         15        0.44       94.48
       7990 |         15        0.44       94.92
       7323 |         14        0.41       95.32
       2761 |         13        0.38       95.70
       2836 |         13        0.38       96.08
       3540 |         13        0.38       96.46
       5045 |         13        0.38       96.83
       3640 |         12        0.35       97.18
       4841 |         12        0.35       97.53
       5000 |         11        0.32       97.85
       5812 |         11        0.32       98.17
       3861 |          9        0.26       98.43
       8731 |          9        0.26       98.69
       9995 |          9        0.26       98.95
       2060 |          8        0.23       99.19
       2820 |          8        0.23       99.42
       4899 |          6        0.17       99.59
       3630 |          5        0.15       99.74
       6211 |          3        0.09       99.83
       3944 |          2        0.06       99.88
       6099 |          2        0.06       99.94
       3580 |          1        0.03       99.97
       6200 |          1        0.03      100.00
------------+-----------------------------------
      Total |      3,443      100.00

. replace xrd=0 if rev~=. & xrd==.
(9,585 real changes made)

. gen rdsales=xrd/rev
(81,864 missing values generated)

. sum xrd rev if rdsales~=. & temp==1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
         xrd |      3,434    1012.109    1995.648          0      28837
        revt |      3,434    20889.15    41927.05       .011     433526

. sum xrd if temp==1, d

              Research and Development Expense
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%        1.355              0
10%        9.395              0       Obs               3,444
25%       43.094              0       Sum of wgt.       3,444

50%      207.868                      Mean           1009.387
                        Largest       Std. dev.      1993.391
75%     963.4205          16625
90%     3200.439          21419       Variance        3973607
95%         5151          22620       Skewness       4.131199
99%         9275          28837       Kurtosis       30.71166

. sum rdsales if temp==1, d

                           rdsales
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%     .0012154              0
10%     .0080979              0       Obs               3,434
25%     .0302889              0       Sum of wgt.       3,434

50%     .0881844                      Mean           .4183371
                        Largest       Std. dev.      9.575185
75%     .1667157          43.44
90%     .2497553       138.7969       Variance       91.68418
95%     .3353724       211.0156       Skewness       44.43082
99%     .7892891            496       Kurtosis       2171.981

. 
. * Table A-17, Panel B
. 
. sum rdsales if temp==1 [w=rev], d
(analytic weights assumed)

                           rdsales
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%     .0006273              0
10%     .0024584              0       Obs               3,434
25%     .0115326              0       Sum of wgt.    71733341

50%     .0362234                      Mean           .0484514
                        Largest       Std. dev.        .05292
75%     .0578585          43.44
90%     .1311494       138.7969       Variance       .0028005
95%     .1546319       211.0156       Skewness       205.2567
99%     .2154712            496       Kurtosis        1453815

. 
. sort patent_id

. egen count=count (app_year), by(patent_id)

. bys patent_id: drop if _n~=1
(18,256 observations deleted)

. save temp, replace
file temp.dta saved

. use all_patent_data

. merge 1:1 patent_id using temp, keepusing(patent_id)

    Result                      Number of obs
    -----------------------------------------
    Not matched                     2,769,409
        from master                 2,695,336  (_merge==1)
        from using                     74,073  (_merge==2)

    Matched                         1,110,358  (_merge==3)
    -----------------------------------------

. drop if _merge==2
(74,073 observations deleted)

. gen newsample=(_merge==3)

. 
. * Table A-18, Panel A 
. 
. ttest mean_cites, by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2695336    7.137471    .0062192    10.21029    7.125281     7.14966
       1 | 1110358    7.411382     .008165    8.603778    7.395379    7.427385
---------+--------------------------------------------------------------------
Combined | 3805694    7.217388     .005008    9.769698    7.207572    7.227203
---------+--------------------------------------------------------------------
    diff |           -.2739115     .011016               -.2955025   -.2523204
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -24.8648
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest weighted_cite, by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2683579    1.013313    .0018528    3.035243    1.009682    1.016945
       1 | 1108881    .9677803    .0030687    3.231471    .9617657    .9737949
---------+--------------------------------------------------------------------
Combined | 3792460           1    .0015888    3.093975    .9968861    1.003114
---------+--------------------------------------------------------------------
    diff |            .0455332    .0034928                .0386875    .0523788
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  13.0365
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest kogan, by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 376,385    18.22336    .0779058    47.79537    18.07067    18.37606
       1 | 949,284    9.686264    .0239144    23.30011    9.639392    9.733135
---------+--------------------------------------------------------------------
Combined | 1325669    12.11012    .0281724    32.43701    12.05491    12.16534
---------+--------------------------------------------------------------------
    diff |              8.5371     .062039                8.415506    8.658695
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = 137.6087
H0: diff = 0                                     Degrees of freedom =  1.3e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. gen SF=(csa_title=="San Jose-San Francisco-Oakland, CA")

. ttest SF,by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2695336    .0614168    .0001462    .2400934    .0611302    .0617035
       1 | 1110358    .1201234    .0003085     .325106    .1195187    .1207281
---------+--------------------------------------------------------------------
Combined | 3805694    .0785452    .0001379    .2690276    .0782749    .0788155
---------+--------------------------------------------------------------------
    diff |           -.0587066    .0003019               -.0592983   -.0581149
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -1.9e+02
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. gen NY=(csa_title=="New York-Newark, NY-NJ-CT-PA")

. ttest NY,by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2695336    .0270445    .0000988    .1622131    .0268508    .0272381
       1 | 1110358    .0384966    .0001826    .1923919    .0381387    .0388544
---------+--------------------------------------------------------------------
Combined | 3805694    .0303858     .000088    .1716464    .0302133    .0305582
---------+--------------------------------------------------------------------
    diff |           -.0114521    .0001935               -.0118313   -.0110729
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t = -59.1931
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. ttest app_date, by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2695336    17895.46     1.11021    1822.685    17893.29    17897.64
       1 | 1110358    17827.94    1.685159    1775.711    17824.64    17831.24
---------+--------------------------------------------------------------------
Combined | 3805694    17875.76    .9274904    1809.366    17873.95    17877.58
---------+--------------------------------------------------------------------
    diff |            67.52195     2.04006                63.52351     71.5204
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  33.0980
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest grant_date, by(newsample)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. err.   Std. dev.   [95% conf. interval]
---------+--------------------------------------------------------------------
       0 | 2695336    19012.19    1.094647    1797.135    19010.04    19014.33
       1 | 1110358    19021.16    1.607001    1693.354    19018.01    19024.31
---------+--------------------------------------------------------------------
Combined | 3805694     19014.8    .9060246     1767.49    19013.03    19016.58
---------+--------------------------------------------------------------------
    diff |           -8.970348    1.993126               -12.87681   -5.063891
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -4.5006
H0: diff = 0                                     Degrees of freedom =  3.8e+06

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 1.0000

. egen count=count(patent_id), by(cpc_subclass newsample)

. egen countall=count(patent_id), by(newsample)

. gen share=count/countall

. drop count countall

. bys cpc_subclass newsample: drop if _n~=1
(3,804,481 observations deleted)

. sort cpc_subclass newsample

. bys cpc_subclass: gen diff=share[_n]-share[_n-1]
(629 missing values generated)

. by cpc_subclass: drop if diff[_n]==. & diff[_n+1]~=.
(584 observations deleted)

. replace diff=share if newsample==1 & diff==.
(0 real changes made)

. replace diff=-share if newsample==0 & diff==.
(45 real changes made)

. sort diff

. 
. * Table A-18, Panel B
. 
. list cpc_subclass diff in 1/10

     +----------------------+
     | cpc_su~s        diff |
     |----------------------|
  1. | A61K       -.0259595 |
  2. | C07D       -.0183356 |
  3. | A61B       -.0181885 |
  4. | G01N        -.011693 |
  5. | C07K       -.0113655 |
     |----------------------|
  6. | A61F       -.0103876 |
  7. | C12N       -.0094578 |
  8. | A61M       -.0094387 |
  9. | A63B       -.0082707 |
 10. | B65D       -.0072069 |
     +----------------------+

. list cpc_subclass diff in -10/l

     +---------------------+
     | cpc_su~s       diff |
     |---------------------|
620. | H04M       .0077621 |
621. | G06T       .0085334 |
622. | H04B       .0093192 |
623. | G11C       .0105967 |
624. | G11B       .0123827 |
     |---------------------|
625. | H04N       .0280319 |
626. | H01L       .0314182 |
627. | H04W       .0345426 |
628. | H04L       .0626981 |
629. | G06F       .1217132 |
     +---------------------+

. 
. 
. log close
      name:  <unnamed>
       log:  /Users/peterdonets/Library/CloudStorage/Dropbox/Replication File for LSSS/replication files PD/log/complete
> codebase.log
  log type:  text
 closed on:  18 May 2023, 11:22:39
------------------------------------------------------------------------------------------------------------------------
